US20050138015A1 - High load SQL driven statistics collection - Google Patents
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- US20050138015A1 US20050138015A1 US10/936,427 US93642704A US2005138015A1 US 20050138015 A1 US20050138015 A1 US 20050138015A1 US 93642704 A US93642704 A US 93642704A US 2005138015 A1 US2005138015 A1 US 2005138015A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2453—Query optimisation
- G06F16/24534—Query rewriting; Transformation
- G06F16/24549—Run-time optimisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/217—Database tuning
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/99931—Database or file accessing
- Y10S707/99932—Access augmentation or optimizing
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/99931—Database or file accessing
- Y10S707/99933—Query processing, i.e. searching
- Y10S707/99934—Query formulation, input preparation, or translation
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/99941—Database schema or data structure
- Y10S707/99944—Object-oriented database structure
Definitions
- This invention is related to the field of electronic database management systems.
- SQL tuning is a very critical aspect of database performance tuning.
- DBA database administrator
- an application developer performs the tuning process.
- it is often a very challenging task.
- the query optimizer relies on statistics of the query objects to function properly, it is important that proper statistics are gathered and kept up to date upon data and schema changes.
- the problem is that the statistics are potentially expensive to collect. This is especially true if complex data statistics are supported by the database system, like multi-column histograms, either within or across tables. In this context, it is unrealistic to collect all possible data statistics since the number is virtually unlimited. Even without complex statistics, few database systems can afford to collect histogram statistics on every skewed column.
- a method for receiving a database query language statement and statistics information about the statement at an optimizer, and identifying an inaccurate statistic for the statement, is disclosed.
- FIG. 3 represents an illustration of the automatic statistics collection process.
- each high load query is auto-tuned with an automatic SQL tuning optimizer as shown in FIG. 1 .
- the maximum set of statistic objects to create is analyzed. If the sum of the estimated creation time for these objects is less than the time constraint, all these statistics can be collected. Otherwise only a subset is collected. The subset can be determined using a knapsack based approach. The weight of each object is the time to create a statistic object while the benefit of creating the statistic object is computed based on the overall improvement of the SQL workload.
- a profiling process is performed by the optimizer during the tuning process to adjust statistics that are used in generating an execution plan for a SQL statement.
- the profiling process verifies that statistics are not missing or stale, validates the estimates made by the query optimizer for intermediate results, and determines the correct optimizer settings.
- the Automatic Tuning Optimizer builds a SQL Profile from the tuning information it generates during the statistics analysis (e.g., provides missing statistics for an object), validation of intermediate results estimate, and detection of the best setting for optimizer parameters. When a SQL Profile is built, the Automatic Tuning Optimizer generates a user recommendation to accept a SQL profile.
- the goal of statistics analysis is to verify that statistics are not missing or stale.
- the query optimizer logs the types of statistics that are actually used during the plan generation process, in preparation for the verification process. For example, when a SQL statement contains an equality predicate, it logs the column number of distinct values, whereas for a range predicate it logs the minimum and maximum column values information.
- the query optimizer checks if each of these statistics is available on the associated query object (i.e. table, index or materialized view). If the statistic is available then it verifies whether the statistic is up-to-date. To verify the accuracy of a statistic, it samples data from the corresponding query object and compares it to the statistic.
- the query optimizer will generate auxiliary information to supply the missing statistic. If a statistic is available but stale, it will generate auxiliary information to compensate for staleness.
- One feature of a cost-based query optimizer is its ability to derive the size of intermediate results. For example, the optimizer estimates the number of rows from applying table filters when deciding which join algorithm to pick.
- Wrong estimates can be caused by a combination of the following factors:
- the data distribution of the column used in the predicate is skewed, and there is no histogram, leading the optimizer to assume a uniform data distribution, or
- the data in column values is correlated but the optimizer is not aware of it, causing the optimizer to assume data independence.
- the automatic statistics collection process tunes high load SQL statements in a SQL tuning set using the automatic SQL Tuning optimizer.
- the optimizer automatically tunes each SQL statement by profiling it and by recommending other tuning actions to the end user.
- FIG. 3 represents an illustration of the SQL tuning process.
- each query in the SQL tuning set is first auto-tuned with an automatic SQL tuning optimizer, 310 . Every time an error is made when estimating the cardinality of an intermediate result, 320 , the SQL-driven statistics collection component attempts to determine the cause of that mistake, i.e. the process determines if a missing statistic is causing that particular mistake, 330 .
- the maximum set of statistic objects to create is analyzed. If the sum of the estimated creation time for these objects is less than the time constraint, all these statistics can be collected, 350 . Otherwise only a subset is collected. The subset can be determined using a knapsack based approach. The weight of each object is the time to create a statistic object while the benefit of creating the statistic object is computed based on the overall improvement of the SQL workload.
- FIG. 4 is a block diagram of a computer system 400 suitable for implementing an embodiment of automatically collecting statistics to improve the execution plan of a high load SQL statement.
- Computer system 400 includes a bus 402 or other communication mechanism for communicating information, which interconnects subsystems and devices, such as processor 404 , system memory 406 (e.g., RAM), static storage device 408 (e.g., ROM), disk drive 410 (e.g., magnetic or optical), communication interface 412 (e.g., modem or ethernet card), display 414 (e.g., CRT or LCD), input device 416 (e.g., keyboard), and cursor control 418 (e.g., mouse or trackball).
- processor 404 includes a bus 402 or other communication mechanism for communicating information, which interconnects subsystems and devices, such as processor 404 , system memory 406 (e.g., RAM), static storage device 408 (e.g., ROM), disk drive 410 (e.g., magnetic or optical), communication interface 412
- computer system 400 performs specific operations by processor 404 executing one or more sequences of one or more instructions contained in system memory 406 .
- Such instructions may be read into system memory 406 from another computer readable medium, such as static storage device 408 or disk drive 410 .
- static storage device 408 or disk drive 410 may be used in place of or in combination with software instructions to implement the invention.
- Non-volatile media includes, for example, optical or magnetic disks, such as disk drive 410 .
- Volatile media includes dynamic memory, such as system memory 406 .
- Transmission media includes coaxial cables, copper wire, and fiber optics, including wires that comprise bus 402 . Transmission media can also take the form of acoustic or light waves, such as those generated during radio wave and infrared data communications.
- Computer readable media includes, for example, floppy disk, flexible disk, hard disk, magnetic tape, any other magnetic medium, CD-ROM, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, RAM, PROM, EPROM, FLASH-EPROM, any other memory chip or cartridge, carrier wave, or any other medium from which a computer can read.
Abstract
A method for receiving a database query language statement and statistics information about the statement at an optimizer, and identifying an inaccurate statistic for the statement, is disclosed.
Description
- This application claims the benefit of U.S. Provisional Application No. 60/500,490, filed Sep. 6, 2003, which is incorporated herein by reference in its entirety. This application is related to co-pending applications “SQL TUNING SETS,” Attorney Docket No. OI7036272001; “AUTO-TUNING SQL STATEMENTS,” Attorney Docket No. OI7037042001; “SQL PROFILE,” Attorney Docket No. OI7037052001; “GLOBAL HINTS,” Attorney Docket No. OI7037062001; “SQL TUNING BASE,” Attorney Docket No. OI7037072001; “AUTOMATIC LEARNING OPTIMIZER,” Attorney Docket No. OI7037082001; “AUTOMATIC PREVENTION OF RUN-AWAY QUERY EXECUTION,” Attorney Docket No. OI7037092001; “METHOD FOR INDEX TUNING OF A SQL STATEMENT, AND INDEX MERGING FOR A MULTI-STATEMENT SQL WORKLOAD, USING A COST-BASED RELATIONAL QUERY OPTIMIZER,” Attorney Docket No. 017037102001; “SQL STRUCTURE ANALYZER,” Attorney Docket No. OI7037112001; “AUTOMATIC SQL TUNING ADVISOR,” Attorney Docket No. OI7037132001, all of which are filed Sep. 7, 2004 and are incorporated herein by reference in their entirety.
- This invention is related to the field of electronic database management systems.
- SQL tuning is a very critical aspect of database performance tuning. Typically the database administrator (DBA) or an application developer performs the tuning process. However, it is often a very challenging task. First, it requires a high level of expertise in several complex areas: query optimization, access design, and SQL design. Second, it is a time consuming process because each statement is unique and needs to be tuned individually. Third, it requires an intimate knowledge of the database as well as the application. Finally, the SQL tuning activity is a continuous task because the SQL workload and the database are always changing.
- For example, because the query optimizer relies on statistics of the query objects to function properly, it is important that proper statistics are gathered and kept up to date upon data and schema changes. The problem is that the statistics are potentially expensive to collect. This is especially true if complex data statistics are supported by the database system, like multi-column histograms, either within or across tables. In this context, it is unrealistic to collect all possible data statistics since the number is virtually unlimited. Even without complex statistics, few database systems can afford to collect histogram statistics on every skewed column.
- Hence only a subset of the statistics can generally be collected for a given database system and the problem is to determine what is this appropriate subset. It is defined as the one which gives the best improvement quality of execution plans while, at the same time, being fast enough to collect (generally the DBA can dedicate at most few hours per day or per week to refresh optimizer statistics). It is unrealistic to expect that the DBA or the application developer will be able to determine this appropriate subset since he will have to know which data statistics are really needed by the query optimizer for his database system. This problem is even worse since the appropriate subset might fluctuate overtime as the SQL workload changes.
- A method for receiving a database query language statement and statistics information about the statement at an optimizer, and identifying an inaccurate statistic for the statement, is disclosed.
-
FIG. 1 shows the Automatic SQL Tuning architecture used in the automatic collection process. -
FIG. 2 shows the process flow of the creation and use of a SQL Profile for the process. -
FIG. 3 represents an illustration of the automatic statistics collection process. -
FIG. 4 is a block diagram of a computer system suitable for implementing an nt of the automatic statistics collection process. - Overview
- The embodiments of the invention are described using the term “SQL”, however, the invention is not limited to just this exact database query language, and indeed may be used in conjunction with other database query languages and constructs.
- To automatically determine which set of statistics would help the query optimizer improve the execution plan for a SQL statement, each high load query is auto-tuned with an automatic SQL tuning optimizer as shown in
FIG. 1 . Every time an error is made when estimating the cardinality of an intermediate result, the SQL-driven statistics collection component attempts to determine the cause of that mistake, i.e. the process determines if a missing statistic is causing that particular mistake. For example, if the query has a predicate t1.c1.=5 and the optimizer makes a mistake when it computes the selectivity of the predicate, the SQL-driven statistics collection component will determine that a histogram is missing on column t1.c1. A new entry will be created for that histogram. The process will also record the query associated with the statistic, plus compute an estimate of the time to create that histogram. - This process will be repeated for every query in the SQL tuning set. At the end, the maximum set of statistic objects to create is analyzed. If the sum of the estimated creation time for these objects is less than the time constraint, all these statistics can be collected. Otherwise only a subset is collected. The subset can be determined using a knapsack based approach. The weight of each object is the time to create a statistic object while the benefit of creating the statistic object is computed based on the overall improvement of the SQL workload.
- Automatic SQL Tune Advisor Architecture
- The Automatic SQL tuning process is implemented by the Automatic Tuning Optimizer, which performs several tuning analyses during the process. The output of a tuning analysis is a set of tuning recommendations, which may be presented to the user.
FIG. 1 shows the Automatic SQL Tuning architecture and the functional relationship between its two sub-components. The SQLtune advisor 110 receives a SQLstatement 117 and information to tune the statement. The information can be related to missing or stale statistics, 120. The information may be a set of tuning hints stored in SQLprofile 130. The information may be related tomissing indexes 140. Also, the information may be about the construct of the SQLstatement 150. Thetune advisor 110 provides the statement and its related information to auto-tuningoptimizer 115. The optimizer automatically tunes the statement with the information by performing auto-tuning processes. Thestatistics analyzer 160 generates adjustment factors to correct missing or stale statistics. The SQLprofiler 165 generates tuning hints for the statement in the form of a profile. Theaccess path analyzer 170 generates indexes. TheSQL structure analyzer 175 generates recommendations for rewriting the statement. - SQL Profiling
- A profiling process is performed by the optimizer during the tuning process to adjust statistics that are used in generating an execution plan for a SQL statement. The profiling process verifies that statistics are not missing or stale, validates the estimates made by the query optimizer for intermediate results, and determines the correct optimizer settings. The Automatic Tuning Optimizer builds a SQL Profile from the tuning information it generates during the statistics analysis (e.g., provides missing statistics for an object), validation of intermediate results estimate, and detection of the best setting for optimizer parameters. When a SQL Profile is built, the Automatic Tuning Optimizer generates a user recommendation to accept a SQL profile.
- Statistics Analysis
- The goal of statistics analysis is to verify that statistics are not missing or stale. The query optimizer logs the types of statistics that are actually used during the plan generation process, in preparation for the verification process. For example, when a SQL statement contains an equality predicate, it logs the column number of distinct values, whereas for a range predicate it logs the minimum and maximum column values information.
- Once the logging of used statistics is complete, the query optimizer checks if each of these statistics is available on the associated query object (i.e. table, index or materialized view). If the statistic is available then it verifies whether the statistic is up-to-date. To verify the accuracy of a statistic, it samples data from the corresponding query object and compares it to the statistic.
- If a statistic is found to be missing, the query optimizer will generate auxiliary information to supply the missing statistic. If a statistic is available but stale, it will generate auxiliary information to compensate for staleness.
- Estimates Analysis
- One feature of a cost-based query optimizer is its ability to derive the size of intermediate results. For example, the optimizer estimates the number of rows from applying table filters when deciding which join algorithm to pick.
- One factor that causes the optimizer to generate a sub-optimal plan is wrong estimate of intermediate result sizes. Wrong estimates can be caused by a combination of the following factors: The predicate (filter or join) is too complex to use standard statistical methods to derive the number of rows (e.g., the columns are compared thru a complex expression like (a*b)/c=10), The data distribution of the column used in the predicate is skewed, and there is no histogram, leading the optimizer to assume a uniform data distribution, or The data in column values is correlated but the optimizer is not aware of it, causing the optimizer to assume data independence.
- During SQL Profiling, the Automatic Tuning Optimizer validates the estimates made by the query optimizer, and compensates for missing information or wrong estimates. The validation process may involve running part of the query on a sample of the input data.
- Parameter Settings Analysis
- The Automatic Tuning Optimizer uses the past execution history of a SQL statement to determine the correct optimizer settings. For example, if the execution history shows that a SQL statement is only partially executed in the majority of times then the appropriate setting will be to optimize it for first n rows, where n is derived from the execution history. This constitutes a customized parameter setting for the SQL statement. (Note that past execution statistics are available in the Automatic Workload Repository (AWR) presented later).
- SQL Profile
- The tuning information produced from the above three analyses is stored in a SQL Profile. Once a SQL Profile is created, it is used in conjunction with the existing statistics by the compiler to produce a well-tuned plan for the corresponding SQL statement.
FIG. 2 shows the process flow of the creation and use of a SQL Profile. The process can have two separate phases: an Automatic SQL Tuning phase, and a regular optimization phase. During the Automatic SQL Tuning phase, a DBA selects aSQL statement 210 and runs the SQL Tuning Advisor. The SQL Tuning Advisor invokes the Automatic Tuning Optimizer to generate tuning recommendations, 220. The Automatic Tuning Optimizer generates a SQL Profile along with other recommendations, 230. After a SQL Profile is built, it is stored in the data dictionary, once it is accepted by the user, 240. - Later, during the regular optimization phase, a user issues the same SQL statement, 250. The query optimizer finds the matching SQL profiles from the data dictionary, 260, and uses the SQL profile information to build a well-tuned execution plan, 270. The use of SQL Profiles is completely transparent to the user.
- The creation and use of a SQL Profile doesn't require changes to the application source code. Therefore, SQL profiling provides a way to tune SQL statements issued from packaged applications where the users have no access to or control over the application source code.
- Automatic Statistic Collection Process
- The automatic statistics collection process tunes high load SQL statements in a SQL tuning set using the automatic SQL Tuning optimizer. The optimizer automatically tunes each SQL statement by profiling it and by recommending other tuning actions to the end user.
FIG. 3 represents an illustration of the SQL tuning process. To determine which set of statistics would help the query optimizer, each query in the SQL tuning set is first auto-tuned with an automatic SQL tuning optimizer, 310. Every time an error is made when estimating the cardinality of an intermediate result, 320, the SQL-driven statistics collection component attempts to determine the cause of that mistake, i.e. the process determines if a missing statistic is causing that particular mistake, 330. For example, if the query has a predicate t1.c1.=5 and the optimizer makes a mistake when it computes the selectivity of the predicate, the SQL-driven statistics collection component will determine that a histogram is missing on column t1.c1. A new entry in a list of missing or erroneous statistics will be created for that histogram, 340. The process will also record the query associated with the statistic, plus compute an estimate of the time to create that histogram, 350. - This process will be repeated for every query in the SQL tuning set. At the end, the maximum set of statistic objects to create is analyzed. If the sum of the estimated creation time for these objects is less than the time constraint, all these statistics can be collected, 350. Otherwise only a subset is collected. The subset can be determined using a knapsack based approach. The weight of each object is the time to create a statistic object while the benefit of creating the statistic object is computed based on the overall improvement of the SQL workload.
- Accepting SQL profile recommendations closes an iteration of the SQL tuning loop; SQL profiling will most likely improve the execution plan of the targeted set of SQL statements, hence reducing their overall performance impact on the system. This will be reflected in the performance measurements being collected. The next tuning cycle can then begin with a different set of high-load SQL statements. The process can be repeated several times until the desired performance level is achieved.
- The Automatic SQL Tuning process, which is integrated with the query optimizer, provides a manageability framework for a self-managing database to automatically collect statistics for high-load SQL statements. The Automatic SQL Tuning process tunes SQL statements and produces a set of comprehensive tuning recommendations. In addition to recommendations, it may also build a SQL Profile to store tuning hints for the statement. The user may decide whether to accept the recommendations. Once a SQL Profile is created, the query optimizer will use it to generate a well-tuned plan for the corresponding SQL statement. A tuning object called the SQL Tuning Set provides a store for a SQL workload to be automatically tuned. With the automatic tuning process, automatic tuning results can scale over a large number of queries and can evolve over time with changes in the application workload and the underlying data. Automatic SQL tuning is also far cheaper than manual tuning. Together, these reasons position automatic SQL tuning as an effective and economical alternative to manual tuning.
-
FIG. 4 is a block diagram of acomputer system 400 suitable for implementing an embodiment of automatically collecting statistics to improve the execution plan of a high load SQL statement.Computer system 400 includes abus 402 or other communication mechanism for communicating information, which interconnects subsystems and devices, such asprocessor 404, system memory 406 (e.g., RAM), static storage device 408 (e.g., ROM), disk drive 410 (e.g., magnetic or optical), communication interface 412 (e.g., modem or ethernet card), display 414 (e.g., CRT or LCD), input device 416 (e.g., keyboard), and cursor control 418 (e.g., mouse or trackball). - According to one embodiment of the invention,
computer system 400 performs specific operations byprocessor 404 executing one or more sequences of one or more instructions contained insystem memory 406. Such instructions may be read intosystem memory 406 from another computer readable medium, such asstatic storage device 408 ordisk drive 410. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement the invention. - The term “computer readable medium” as used herein refers to any medium that participates in providing instructions to
processor 404 for execution. Such a medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media includes, for example, optical or magnetic disks, such asdisk drive 410. Volatile media includes dynamic memory, such assystem memory 406. Transmission media includes coaxial cables, copper wire, and fiber optics, including wires that comprisebus 402. Transmission media can also take the form of acoustic or light waves, such as those generated during radio wave and infrared data communications. - Common forms of computer readable media includes, for example, floppy disk, flexible disk, hard disk, magnetic tape, any other magnetic medium, CD-ROM, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, RAM, PROM, EPROM, FLASH-EPROM, any other memory chip or cartridge, carrier wave, or any other medium from which a computer can read.
- In an embodiment of the invention, execution of the sequences of instructions to practice the invention is performed by a
single computer system 400. According to other embodiments of the invention, two ormore computer systems 400 coupled by communication link 420 (e.g., LAN, PTSN, or wireless network) may perform the sequence of instructions to practice the invention in coordination with one another.Computer system 400 may transmit and receive messages, data, and instructions, including program, i.e., application code, throughcommunication link 420 andcommunication interface 412. Received program code may be executed byprocessor 404 as it is received, and/or stored indisk drive 410, or other non-volatile storage for later execution. - In the foregoing specification, the invention has been described with reference to specific embodiments thereof. It will, however, be evident that various modifications and changes may be made thereto without departing from the broader spirit and scope of the invention. The specification and drawings are, accordingly, to be regarded in an illustrative rather than restrictive sense.
Claims (18)
1. A method comprising:
receiving a database query language statement and execution statistics information about the statement at an optimizer; and
identifying one or more inaccurate or missing statistics for the statement.
2. The method of claim 1 , wherein identifying further comprises:
identifying a problem with an execution plan of each statement; and
determining that one or more inaccurate or missing statistics causes the problem of the execution plan.
3. The method of claim 2 , further comprising:
creating an entry for the inaccurate or missing statistic in a collection list.
4. The method of claim 3 , further comprising:
automatically collecting statistics for each entry in the collection list.
5. The method of claim 1 , wherein receiving the statement further comprises:
identifying high load statements;
storing the high load statements in a tuning set; and
sending each high load statement in the tuning set to the optimizer.
6. The method of claim 1 , wherein the database query language statement is a SQL statement.
7. An apparatus comprising:
means for receiving a database query language statement and execution statistics information about the statement at an optimizer; and
means for identifying one or more inaccurate or missing statistics for the statement.
8. The apparatus of claim 7 , wherein said means for identifying further comprises:
means for identifying a problem with an execution plan of each statement; and
means for determining that one or more inaccurate or missing statistics causes the problem of the execution plan.
9. The apparatus of claim 8 , further comprising:
means for creating an entry for the inaccurate statistic in a collection list.
10. The apparatus of claim 9 , further comprising:
means for automatically collecting statistics for each entry in the collection list.
11. The apparatus of claim 7 , wherein said means for receiving the statement further comprises:
means for identifying high load statements;
means for storing the high load statements in a tuning set; and
means for sending each high load statement in the tuning set to the optimizer.
12. The apparatus of claim 7 , wherein the database query language statement is a SQL statement.
13. A computer readable medium storing a computer program of instructions which, when executed by a processing system, cause the system to perform a method comprising:
receiving a database query language statement and execution statistics information about the statement at an optimizer; and
identifying one or more missing or inaccurate statistics for the statement.
14. The medium of claim 13 , wherein identifying further comprises:
identifying a problem with an execution plan of each statement; and
determining that one or more inaccurate or missing statistics causes the problem of the execution plan.
15. The medium of claim 14 , wherein the instructions, when executed, further perform the method comprising:
creating an entry for the inaccurate statistic in a collection list.
16. The medium of claim 15 , wherein the instructions, when executed, further perform the method comprising:
automatically collecting statistics for each entry in the collection list.
17. The medium of claim 13 , wherein receiving the statement further comprises:
identifying high load statements;
storing the high load statements in a tuning set; and
sending each high load statement in the tuning set to the optimizer.
18. The medium of claim 13 , wherein the database query language statement is a SQL statement.
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US10/936,469 Active 2026-02-15 US8825629B2 (en) | 2003-09-06 | 2004-09-07 | Method for index tuning of a SQL statement, and index merging for a multi-statement SQL workload, using a cost-based relational query optimizer |
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US10/936,205 Active 2025-11-28 US7664730B2 (en) | 2003-09-06 | 2004-09-07 | Method and system for implementing a SQL profile |
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Cited By (23)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20050119999A1 (en) * | 2003-09-06 | 2005-06-02 | Oracle International Corporation | Automatic learning optimizer |
US20050210461A1 (en) * | 2004-03-17 | 2005-09-22 | Oracle International Corporation | Method and mechanism for performing a rolling upgrade of distributed computer software |
US20060080285A1 (en) * | 2004-10-13 | 2006-04-13 | Sybase, Inc. | Database System with Methodology for Parallel Schedule Generation in a Query Optimizer |
US20060149695A1 (en) * | 2004-12-30 | 2006-07-06 | International Business Machines Corporation | Management of database statistics |
US20060195416A1 (en) * | 2005-02-28 | 2006-08-31 | Ewen Stephan E | Method and system for providing a learning optimizer for federated database systems |
US20060230016A1 (en) * | 2005-03-29 | 2006-10-12 | Microsoft Corporation | Systems and methods for statistics over complex objects |
US20080126393A1 (en) * | 2006-11-29 | 2008-05-29 | Bossman Patrick D | Computer program product and system for annotating a problem sql statement for improved understanding |
US20080133454A1 (en) * | 2004-10-29 | 2008-06-05 | International Business Machines Corporation | System and method for updating database statistics according to query feedback |
US20090018992A1 (en) * | 2007-07-12 | 2009-01-15 | Ibm Corporation | Management of interesting database statistics |
US20090030875A1 (en) * | 2004-01-07 | 2009-01-29 | International Business Machines Corporation | Statistics management |
US20090077016A1 (en) * | 2007-09-14 | 2009-03-19 | Oracle International Corporation | Fully automated sql tuning |
US20090106306A1 (en) * | 2007-10-17 | 2009-04-23 | Dinesh Das | SQL Execution Plan Baselines |
US20090248621A1 (en) * | 2008-03-31 | 2009-10-01 | Benoit Dageville | Method and mechanism for out-of-the-box real-time sql monitoring |
US20090265329A1 (en) * | 2008-04-17 | 2009-10-22 | International Business Machines Corporation | System and method of data caching for compliance storage systems with keyword query based access |
US7788285B2 (en) | 2004-05-14 | 2010-08-31 | Oracle International Corporation | Finer grain dependency tracking for database objects |
US8903805B2 (en) | 2010-08-20 | 2014-12-02 | Oracle International Corporation | Method and system for performing query optimization using a hybrid execution plan |
US20150242464A1 (en) * | 2014-02-24 | 2015-08-27 | Red Hat, Inc. | Source query caching as fault prevention for federated queries |
US10409701B2 (en) * | 2016-08-11 | 2019-09-10 | Salesforce.Com, Inc. | Per-statement monitoring in a database environment |
US10621064B2 (en) | 2014-07-07 | 2020-04-14 | Oracle International Corporation | Proactive impact measurement of database changes on production systems |
US11281770B2 (en) | 2016-08-11 | 2022-03-22 | Salesforce.Com, Inc. | Detection of structured query language (SQL) injection events using simple statistical analysis |
US11327932B2 (en) | 2017-09-30 | 2022-05-10 | Oracle International Corporation | Autonomous multitenant database cloud service framework |
US11386058B2 (en) | 2017-09-29 | 2022-07-12 | Oracle International Corporation | Rule-based autonomous database cloud service framework |
US20230065855A1 (en) * | 2021-08-26 | 2023-03-02 | International Business Machines Corporation | Dynamical database system resource balance |
Families Citing this family (301)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2001093105A2 (en) * | 2000-05-26 | 2001-12-06 | Computer Associates Think, Inc. | System and method for automatically generating database queries |
US8374966B1 (en) | 2002-08-01 | 2013-02-12 | Oracle International Corporation | In memory streaming with disk backup and recovery of messages captured from a database redo stream |
US7130838B2 (en) * | 2003-09-11 | 2006-10-31 | International Business Machines Corporation | Query optimization via a partitioned environment |
US7401069B2 (en) * | 2003-09-11 | 2008-07-15 | International Business Machines Corporation | Background index bitmapping for faster query performance |
US7321888B2 (en) * | 2003-09-11 | 2008-01-22 | International Business Machines Corporation | Method and system for dynamic join reordering |
US7552110B2 (en) * | 2003-09-22 | 2009-06-23 | International Business Machines Corporation | Method for performing a query in a computer system to retrieve data from a database |
US7188098B2 (en) * | 2003-09-24 | 2007-03-06 | International Business Machines Corporation | Query transformation for union all view join queries using join predicates for pruning and distribution |
US7340448B2 (en) * | 2003-11-13 | 2008-03-04 | International Business Machines Corporation | Method, apparatus, and computer program product for implementing enhanced query governor functions |
US7562094B1 (en) * | 2003-12-31 | 2009-07-14 | Precise Software Solutions, Inc. | Object-level database performance management |
US8775412B2 (en) * | 2004-01-08 | 2014-07-08 | International Business Machines Corporation | Method and system for a self-healing query access plan |
US7454404B2 (en) * | 2004-02-26 | 2008-11-18 | International Business Machines Corporation | Method of addressing query scheduling and system resource requirements |
US20050192937A1 (en) * | 2004-02-26 | 2005-09-01 | International Business Machines Corporation | Dynamic query optimization |
US7606792B2 (en) * | 2004-03-19 | 2009-10-20 | Microsoft Corporation | System and method for efficient evaluation of a query that invokes a table valued function |
US7702627B2 (en) * | 2004-06-22 | 2010-04-20 | Oracle International Corporation | Efficient interaction among cost-based transformations |
US20050283471A1 (en) * | 2004-06-22 | 2005-12-22 | Oracle International Corporation | Multi-tier query processing |
US8346761B2 (en) * | 2004-08-05 | 2013-01-01 | International Business Machines Corporation | Method and system for data mining for automatic query optimization |
US7814042B2 (en) * | 2004-08-17 | 2010-10-12 | Oracle International Corporation | Selecting candidate queries |
US8046354B2 (en) * | 2004-09-30 | 2011-10-25 | International Business Machines Corporation | Method and apparatus for re-evaluating execution strategy for a database query |
US20060085375A1 (en) * | 2004-10-14 | 2006-04-20 | International Business Machines Corporation | Method and system for access plan sampling |
US20060085484A1 (en) * | 2004-10-15 | 2006-04-20 | Microsoft Corporation | Database tuning advisor |
US20060085378A1 (en) * | 2004-10-15 | 2006-04-20 | Microsoft Corporation | Schema for physical database tuning |
US7529729B2 (en) * | 2004-10-21 | 2009-05-05 | International Business Machines Corporation | System and method for handling improper database table access |
US7536379B2 (en) * | 2004-12-15 | 2009-05-19 | International Business Machines Corporation | Performing a multiple table join operating based on generated predicates from materialized results |
US20060136358A1 (en) * | 2004-12-21 | 2006-06-22 | Microsoft Corporation | Database tuning advisor graphical tool |
US20060167845A1 (en) * | 2005-01-25 | 2006-07-27 | International Business Machines Corporation | Selection of optimal plans for FIRST-N-ROW queries |
US7567968B2 (en) * | 2005-01-31 | 2009-07-28 | Microsoft Corporation | Integration of a non-relational query language with a relational data store |
US7392266B2 (en) * | 2005-03-17 | 2008-06-24 | International Business Machines Corporation | Apparatus and method for monitoring usage of components in a database index |
US7765200B2 (en) * | 2005-03-25 | 2010-07-27 | International Business Machines Corporation | SQL query problem determination tool |
US7640230B2 (en) * | 2005-04-05 | 2009-12-29 | Microsoft Corporation | Query plan selection control using run-time association mechanism |
US7337167B2 (en) * | 2005-04-14 | 2008-02-26 | International Business Machines Corporation | Estimating a number of rows returned by a recursive query |
US20060242102A1 (en) * | 2005-04-21 | 2006-10-26 | Microsoft Corporation | Relaxation-based approach to automatic physical database tuning |
US7567982B2 (en) * | 2005-08-02 | 2009-07-28 | Glynntech, Inc. | Matrix-connected, artificially intelligent address book system |
US8468152B2 (en) * | 2005-08-04 | 2013-06-18 | International Business Machines Corporation | Autonomic refresh of a materialized query table in a computer database |
US7475056B2 (en) | 2005-08-11 | 2009-01-06 | Oracle International Corporation | Query processing in a parallel single cursor model on multi-instance configurations, using hints |
US7814091B2 (en) * | 2005-09-27 | 2010-10-12 | Oracle International Corporation | Multi-tiered query processing techniques for minus and intersect operators |
US20070073761A1 (en) * | 2005-09-29 | 2007-03-29 | International Business Machines Corporation | Continual generation of index advice |
US7877379B2 (en) * | 2005-09-30 | 2011-01-25 | Oracle International Corporation | Delaying evaluation of expensive expressions in a query |
US7840032B2 (en) * | 2005-10-04 | 2010-11-23 | Microsoft Corporation | Street-side maps and paths |
US7634457B2 (en) * | 2005-10-07 | 2009-12-15 | Oracle International Corp. | Function-based index tuning for queries with expressions |
US7475068B2 (en) * | 2005-10-07 | 2009-01-06 | Oracle International Corp. | Globally optimal and greedy heuristics based approach to access structure selection |
US7840553B2 (en) | 2005-10-07 | 2010-11-23 | Oracle International Corp. | Recommending materialized views for queries with multiple instances of same table |
US8073841B2 (en) | 2005-10-07 | 2011-12-06 | Oracle International Corporation | Optimizing correlated XML extracts |
US20070115916A1 (en) * | 2005-11-07 | 2007-05-24 | Samsung Electronics Co., Ltd. | Method and system for optimizing a network based on a performance knowledge base |
US8069153B2 (en) * | 2005-12-02 | 2011-11-29 | Salesforce.Com, Inc. | Systems and methods for securing customer data in a multi-tenant environment |
CN101131695B (en) * | 2006-08-25 | 2010-05-26 | 北京书生国际信息技术有限公司 | Document file library system and its implementing method |
US8180762B2 (en) * | 2005-12-13 | 2012-05-15 | International Business Machines Corporation | Database tuning methods |
US7882121B2 (en) * | 2006-01-27 | 2011-02-01 | Microsoft Corporation | Generating queries using cardinality constraints |
US7743052B2 (en) * | 2006-02-14 | 2010-06-22 | International Business Machines Corporation | Method and apparatus for projecting the effect of maintaining an auxiliary database structure for use in executing database queries |
US8433712B2 (en) * | 2006-03-01 | 2013-04-30 | Oracle International Corporation | Link analysis for enterprise environment |
US7941419B2 (en) | 2006-03-01 | 2011-05-10 | Oracle International Corporation | Suggested content with attribute parameterization |
US8027982B2 (en) * | 2006-03-01 | 2011-09-27 | Oracle International Corporation | Self-service sources for secure search |
US20070214129A1 (en) * | 2006-03-01 | 2007-09-13 | Oracle International Corporation | Flexible Authorization Model for Secure Search |
US8875249B2 (en) * | 2006-03-01 | 2014-10-28 | Oracle International Corporation | Minimum lifespan credentials for crawling data repositories |
US8005816B2 (en) * | 2006-03-01 | 2011-08-23 | Oracle International Corporation | Auto generation of suggested links in a search system |
US8214394B2 (en) | 2006-03-01 | 2012-07-03 | Oracle International Corporation | Propagating user identities in a secure federated search system |
US8707451B2 (en) | 2006-03-01 | 2014-04-22 | Oracle International Corporation | Search hit URL modification for secure application integration |
US8332430B2 (en) * | 2006-03-01 | 2012-12-11 | Oracle International Corporation | Secure search performance improvement |
US9177124B2 (en) | 2006-03-01 | 2015-11-03 | Oracle International Corporation | Flexible authentication framework |
US8868540B2 (en) * | 2006-03-01 | 2014-10-21 | Oracle International Corporation | Method for suggesting web links and alternate terms for matching search queries |
US20070219973A1 (en) * | 2006-03-15 | 2007-09-20 | International Business Machines Corporation | Dynamic statement processing in database systems |
US7809713B2 (en) * | 2006-03-15 | 2010-10-05 | Oracle International Corporation | Efficient search space analysis for join factorization |
US7644062B2 (en) * | 2006-03-15 | 2010-01-05 | Oracle International Corporation | Join factorization of union/union all queries |
US7945562B2 (en) * | 2006-03-15 | 2011-05-17 | Oracle International Corporation | Join predicate push-down optimizations |
US7676450B2 (en) * | 2006-03-15 | 2010-03-09 | Oracle International Corporation | Null aware anti-join |
DE102006017076B4 (en) * | 2006-04-10 | 2020-04-23 | Lufthansa Systems Gmbh & Co. Kg | Automatic optimization of query processing in database systems |
US20070250517A1 (en) * | 2006-04-20 | 2007-10-25 | Bestgen Robert J | Method and Apparatus for Autonomically Maintaining Latent Auxiliary Database Structures for Use in Executing Database Queries |
US20070250470A1 (en) * | 2006-04-24 | 2007-10-25 | Microsoft Corporation | Parallelization of language-integrated collection operations |
US8838574B2 (en) * | 2006-06-09 | 2014-09-16 | International Business Machines Corporation | Autonomic index creation, modification and deletion |
US8838573B2 (en) * | 2006-06-09 | 2014-09-16 | International Business Machines Corporation | Autonomic index creation |
US20070288489A1 (en) * | 2006-06-09 | 2007-12-13 | Mark John Anderson | Apparatus and Method for Autonomic Index Creation, Modification and Deletion |
US7730080B2 (en) * | 2006-06-23 | 2010-06-01 | Oracle International Corporation | Techniques of rewriting descendant and wildcard XPath using one or more of SQL OR, UNION ALL, and XMLConcat() construct |
US7877373B2 (en) * | 2006-06-30 | 2011-01-25 | Oracle International Corporation | Executing alternative plans for a SQL statement |
US8086598B1 (en) | 2006-08-02 | 2011-12-27 | Hewlett-Packard Development Company, L.P. | Query optimizer with schema conversion |
US10007686B2 (en) * | 2006-08-02 | 2018-06-26 | Entit Software Llc | Automatic vertical-database design |
US20080046473A1 (en) * | 2006-08-15 | 2008-02-21 | Bingjie Miao | Method and System For Using Index Lead Key Self-Join To Take Advantage of Selectivity of Non-Leading Key Columns of an Index |
US8032522B2 (en) * | 2006-08-25 | 2011-10-04 | Microsoft Corporation | Optimizing parameterized queries in a relational database management system |
US7813948B2 (en) * | 2006-08-25 | 2010-10-12 | Sas Institute Inc. | Computer-implemented systems and methods for reducing cost flow models |
US20080065590A1 (en) * | 2006-09-07 | 2008-03-13 | Microsoft Corporation | Lightweight query processing over in-memory data structures |
US8527502B2 (en) * | 2006-09-08 | 2013-09-03 | Blade Makai Doyle | Method, system and computer-readable media for software object relationship traversal for object-relational query binding |
CN101162462A (en) * | 2006-10-11 | 2008-04-16 | 国际商业机器公司 | Tools and method for making prompt |
US8285707B2 (en) * | 2006-11-08 | 2012-10-09 | International Business Machines Corporation | Method of querying relational database management systems |
US7516128B2 (en) * | 2006-11-14 | 2009-04-07 | International Business Machines Corporation | Method for cleansing sequence-based data at query time |
US20080133493A1 (en) * | 2006-12-04 | 2008-06-05 | Michael Bender | Method for maintaining database clustering when replacing tables with inserts |
US7606827B2 (en) * | 2006-12-14 | 2009-10-20 | Ianywhere Solutions, Inc. | Query optimization using materialized views in database management systems |
US8214807B2 (en) * | 2007-01-10 | 2012-07-03 | International Business Machines Corporation | Code path tracking |
US20080178079A1 (en) * | 2007-01-18 | 2008-07-24 | International Business Machines Corporation | Apparatus and method for a graphical user interface to facilitate tuning sql statements |
US8150790B2 (en) * | 2007-01-31 | 2012-04-03 | Microsoft Corporation | Lightweight physical design alerter |
US20080183764A1 (en) * | 2007-01-31 | 2008-07-31 | Microsoft Corporation | Continuous physical design tuning |
US20080196012A1 (en) * | 2007-02-12 | 2008-08-14 | Panaya Ltd. | System and methods for static analysis of large computer programs and for presenting the results of the analysis to a user of a computer program |
US20080215564A1 (en) * | 2007-03-02 | 2008-09-04 | Jon Bratseth | Query rewrite |
US7860899B2 (en) * | 2007-03-26 | 2010-12-28 | Oracle International Corporation | Automatically determining a database representation for an abstract datatype |
US8037112B2 (en) * | 2007-04-23 | 2011-10-11 | Microsoft Corporation | Efficient access of flash databases |
US7870122B2 (en) * | 2007-04-23 | 2011-01-11 | Microsoft Corporation | Self-tuning index for flash-based databases |
US7996392B2 (en) | 2007-06-27 | 2011-08-09 | Oracle International Corporation | Changing ranking algorithms based on customer settings |
US8316007B2 (en) * | 2007-06-28 | 2012-11-20 | Oracle International Corporation | Automatically finding acronyms and synonyms in a corpus |
US8024241B2 (en) * | 2007-07-13 | 2011-09-20 | Sas Institute Inc. | Computer-implemented systems and methods for cost flow analysis |
US7702623B2 (en) * | 2007-07-31 | 2010-04-20 | Oracle International Corporation | Extended cursor sharing |
US7840556B1 (en) * | 2007-07-31 | 2010-11-23 | Hewlett-Packard Development Company, L.P. | Managing performance of a database query |
US7689550B2 (en) * | 2007-07-31 | 2010-03-30 | Oracle International Corporation | Adaptive cursor sharing |
US7644063B2 (en) * | 2007-08-17 | 2010-01-05 | International Business Machines Corporation | Apparatus, system, and method for ensuring query execution plan stability in a database management system |
US8209322B2 (en) * | 2007-08-21 | 2012-06-26 | Oracle International Corporation | Table elimination technique for group-by query optimization |
WO2009032225A1 (en) * | 2007-08-28 | 2009-03-12 | Sugarcrm Inc. | Crm system and method having drilldowns, acls, shared folders, a tracker and a module builder |
US20090070300A1 (en) * | 2007-09-07 | 2009-03-12 | International Business Machines Corporation | Method for Processing Data Queries |
US8776062B2 (en) * | 2007-09-10 | 2014-07-08 | International Business Machines Corporation | Determining desired job plan based on previous inquiries in a stream processing framework |
US8341178B2 (en) * | 2007-09-18 | 2012-12-25 | Oracle International Corporation | SQL performance analyzer |
US8200645B2 (en) * | 2007-09-21 | 2012-06-12 | International Business Machines Corporation | System and method for executing multiple concurrent index-driven table access operations |
US7836036B2 (en) * | 2007-09-21 | 2010-11-16 | International Business Machines Corporation | System and method for estimating distances between multiple index-driven scan operations |
US20090094191A1 (en) * | 2007-10-08 | 2009-04-09 | Microsoft Corporation | Exploiting execution feedback for optimizing choice of access methods |
US9213740B2 (en) * | 2007-10-11 | 2015-12-15 | Sybase, Inc. | System and methodology for automatic tuning of database query optimizer |
US8438152B2 (en) * | 2007-10-29 | 2013-05-07 | Oracle International Corporation | Techniques for bushy tree execution plans for snowstorm schema |
US9740735B2 (en) | 2007-11-07 | 2017-08-22 | Microsoft Technology Licensing, Llc | Programming language extensions in structured queries |
US7996384B2 (en) * | 2007-12-12 | 2011-08-09 | International Business Machines Corporation | Query based rule optimization through rule combination |
US20090171936A1 (en) * | 2007-12-28 | 2009-07-02 | Sybase, Inc. | System, Method, and Computer Program Product for Accelerating Like Conditions |
US8818987B2 (en) * | 2008-01-11 | 2014-08-26 | International Business Machines Corporation | Converting union commands to union all commands |
US8200518B2 (en) | 2008-02-25 | 2012-06-12 | Sas Institute Inc. | Computer-implemented systems and methods for partial contribution computation in ABC/M models |
US8239369B2 (en) * | 2008-03-20 | 2012-08-07 | DBSophic, Ltd. | Method and apparatus for enhancing performance of database and environment thereof |
US20090271360A1 (en) * | 2008-04-25 | 2009-10-29 | Bestgen Robert J | Assigning Plan Volatility Scores to Control Reoptimization Frequency and Number of Stored Reoptimization Plans |
US8312007B2 (en) * | 2008-05-08 | 2012-11-13 | International Business Machines Corporation | Generating database query plans |
US9189047B2 (en) | 2008-05-08 | 2015-11-17 | International Business Machines Corporation | Organizing databases for energy efficiency |
US20090287638A1 (en) * | 2008-05-15 | 2009-11-19 | Robert Joseph Bestgen | Autonomic system-wide sql query performance advisor |
US20090313211A1 (en) * | 2008-06-17 | 2009-12-17 | Ahmad Said Ghazal | Pushing joins across a union |
US10983998B2 (en) * | 2008-06-25 | 2021-04-20 | Microsoft Technology Licensing, Llc | Query execution plans by compilation-time execution |
US7966313B2 (en) * | 2008-06-26 | 2011-06-21 | Microsoft Corporation | Configuration-parametric query optimization |
US7970755B2 (en) * | 2008-07-02 | 2011-06-28 | Oracle Int'l. Corp. | Test execution of user SQL in database server code |
US7970776B1 (en) * | 2008-08-06 | 2011-06-28 | Precise Software Solutions Inc. | Apparatus, method and computer readable medium for identifying and quantifying database disk-sort operations |
US7958112B2 (en) | 2008-08-08 | 2011-06-07 | Oracle International Corporation | Interleaving query transformations for XML indexes |
US8667018B2 (en) * | 2008-08-08 | 2014-03-04 | Oracle International Corporation | Method and system for optimizing row level security in database systems |
US8140548B2 (en) * | 2008-08-13 | 2012-03-20 | Microsoft Corporation | Constrained physical design tuning |
US8060495B2 (en) * | 2008-10-21 | 2011-11-15 | International Business Machines Corporation | Query execution plan efficiency in a database management system |
US20100114976A1 (en) * | 2008-10-21 | 2010-05-06 | Castellanos Maria G | Method For Database Design |
US8135702B2 (en) * | 2008-10-27 | 2012-03-13 | Teradata Us, Inc. | Eliminating unnecessary statistics collections for query optimization |
US8041789B1 (en) * | 2008-10-29 | 2011-10-18 | Hewlett-Packard Development Company, L.P. | System using management server for migration of profiles for device bays in between enclosures |
US7668804B1 (en) | 2008-11-04 | 2010-02-23 | International Business Machines Corporation | Recommending statistical views using cost/benefit metrics |
US8510290B1 (en) * | 2008-12-30 | 2013-08-13 | Teradata Us, Inc. | Index selection in a multi-system database management system |
US8024286B2 (en) * | 2009-01-08 | 2011-09-20 | Teradata Us, Inc. | Independent column detection in selectivity estimation |
US8463806B2 (en) * | 2009-01-30 | 2013-06-11 | Lexisnexis | Methods and systems for creating and using an adaptive thesaurus |
US8805852B2 (en) * | 2009-03-02 | 2014-08-12 | International Business Machines Corporation | Automatic query execution plan management and performance stabilization for workloads |
US8892544B2 (en) * | 2009-04-01 | 2014-11-18 | Sybase, Inc. | Testing efficiency and stability of a database query engine |
US8458167B2 (en) * | 2009-04-01 | 2013-06-04 | International Business Machines Corporation | Client-based index advisor |
US8161017B2 (en) * | 2009-04-03 | 2012-04-17 | International Business Machines Corporation | Enhanced identification of relevant database indices |
US20100287015A1 (en) * | 2009-05-11 | 2010-11-11 | Grace Au | Method for determining the cost of evaluating conditions |
US8229952B2 (en) * | 2009-05-11 | 2012-07-24 | Business Objects Software Limited | Generation of logical database schema representation based on symbolic business intelligence query |
US8417690B2 (en) * | 2009-05-15 | 2013-04-09 | International Business Machines Corporation | Automatically avoiding unconstrained cartesian product joins |
US9836504B2 (en) * | 2009-06-30 | 2017-12-05 | Hewlett Packard Enterprise Development Lp | Query progress estimation based on processed value packets |
US9141664B2 (en) | 2009-08-31 | 2015-09-22 | Hewlett-Packard Development Company, L.P. | System and method for optimizing queries |
US20110211738A1 (en) * | 2009-12-23 | 2011-09-01 | Searete Llc, A Limited Liability Corporation Of The State Of Delaware | Identifying a characteristic of an individual utilizing facial recognition and providing a display for the individual |
US9665620B2 (en) | 2010-01-15 | 2017-05-30 | Ab Initio Technology Llc | Managing data queries |
US8290931B2 (en) * | 2010-02-22 | 2012-10-16 | Hewlett-Packard Development Company, L.P. | Database designer |
US8396873B2 (en) * | 2010-03-10 | 2013-03-12 | Emc Corporation | Index searching using a bloom filter |
US8655894B2 (en) * | 2010-04-26 | 2014-02-18 | Nokia Corporation | Method and apparatus for index generation and use |
US8566307B2 (en) | 2010-04-30 | 2013-10-22 | International Business Machines Corporation | Database query governor with tailored thresholds |
US8332388B2 (en) | 2010-06-18 | 2012-12-11 | Microsoft Corporation | Transformation rule profiling for a query optimizer |
US8688689B2 (en) * | 2010-06-30 | 2014-04-01 | Oracle International Corporation | Techniques for recommending alternative SQL execution plans |
US9256642B2 (en) | 2010-06-30 | 2016-02-09 | Oracle International Corporation | Techniques for recommending parallel execution of SQL statements |
US20120066554A1 (en) * | 2010-09-09 | 2012-03-15 | Microsoft Corporation | Application query control with cost prediction |
US8402119B2 (en) | 2010-09-30 | 2013-03-19 | Microsoft Corporation | Real-load tuning of database applications |
US8938644B2 (en) * | 2010-12-03 | 2015-01-20 | Teradata Us, Inc. | Query execution plan revision for error recovery |
CN102541966A (en) * | 2010-12-30 | 2012-07-04 | 国际商业机器公司 | Method and device for verifying correctness of database system |
US8666970B2 (en) * | 2011-01-20 | 2014-03-04 | Accenture Global Services Limited | Query plan enhancement |
US20120215764A1 (en) * | 2011-02-17 | 2012-08-23 | International Business Machines Corporation | Energy usage and performance query governor |
US9116955B2 (en) | 2011-05-02 | 2015-08-25 | Ab Initio Technology Llc | Managing data queries |
US9934280B2 (en) * | 2011-05-13 | 2018-04-03 | Entit Software Llc | Join order restrictions |
US20120303633A1 (en) * | 2011-05-26 | 2012-11-29 | International Business Machines Corporation | Systems and methods for querying column oriented databases |
US8595238B2 (en) * | 2011-06-22 | 2013-11-26 | International Business Machines Corporation | Smart index creation and reconciliation in an interconnected network of systems |
US9626434B2 (en) | 2011-08-30 | 2017-04-18 | Open Text Sa Ulc | Systems and methods for generating and using aggregated search indices and non-aggregated value storage |
US8868546B2 (en) * | 2011-09-15 | 2014-10-21 | Oracle International Corporation | Query explain plan in a distributed data management system |
US9773032B2 (en) * | 2011-09-30 | 2017-09-26 | Bmc Software, Inc. | Provision of index recommendations for database access |
US8983996B2 (en) * | 2011-10-31 | 2015-03-17 | Yahoo! Inc. | Assisted searching |
CN103164455B (en) * | 2011-12-15 | 2016-08-03 | 百度在线网络技术(北京)有限公司 | The optimization method and device of data base |
US9858313B2 (en) | 2011-12-22 | 2018-01-02 | Excalibur Ip, Llc | Method and system for generating query-related suggestions |
US9037552B2 (en) | 2011-12-27 | 2015-05-19 | Infosys Limited | Methods for analyzing a database and devices thereof |
US8990186B2 (en) * | 2011-12-28 | 2015-03-24 | Teradata Us, Inc. | Techniques for updating join indexes |
US8825631B2 (en) * | 2012-03-27 | 2014-09-02 | Wipro Limited | System and method for improved processing of an SQL query made against a relational database |
US9158814B2 (en) * | 2012-03-30 | 2015-10-13 | International Business Machines Corporation | Obtaining partial results from a database query |
CN103365885B (en) | 2012-03-30 | 2016-12-14 | 国际商业机器公司 | Method and system for database inquiry optimization |
EP2901324B1 (en) | 2012-09-28 | 2019-11-06 | Oracle International Corporation | Adaptive query optimization |
US8856102B2 (en) | 2012-11-07 | 2014-10-07 | International Business Machines Corporation | Modifying structured query language statements |
US9280583B2 (en) * | 2012-11-30 | 2016-03-08 | International Business Machines Corporation | Scalable multi-query optimization for SPARQL |
US9146960B2 (en) * | 2012-12-20 | 2015-09-29 | Teradata Us, Inc. | Adaptive optimization of iterative or recursive query execution by database systems |
US9720966B2 (en) * | 2012-12-20 | 2017-08-01 | Teradata Us, Inc. | Cardinality estimation for optimization of recursive or iterative database queries by databases |
US20140201192A1 (en) * | 2013-01-15 | 2014-07-17 | Syscom Computer Engineering Co. | Automatic data index establishment method |
US10592506B1 (en) * | 2013-02-13 | 2020-03-17 | Amazon Technologies, Inc. | Query hint specification |
US9336272B1 (en) * | 2013-02-13 | 2016-05-10 | Amazon Technologies, Inc. | Global query hint specification |
US8996559B2 (en) | 2013-03-17 | 2015-03-31 | Alation, Inc. | Assisted query formation, validation, and result previewing in a database having a complex schema |
US9367594B2 (en) | 2013-03-29 | 2016-06-14 | International Business Machines Corporation | Determining statistics for cost-based optimization of a workflow |
US9779137B2 (en) | 2013-07-09 | 2017-10-03 | Logicblox Inc. | Salient sampling for query size estimation |
US20150019584A1 (en) * | 2013-07-15 | 2015-01-15 | International Business Machines Corporation | Self-learning java database connectivity (jdbc) driver |
US20150039555A1 (en) * | 2013-08-02 | 2015-02-05 | International Business Machines Corporation | Heuristically modifying dbms environments using performance analytics |
US9262457B2 (en) * | 2013-08-13 | 2016-02-16 | Sybase, Inc. | On-demand hash index |
US9588978B2 (en) | 2013-09-30 | 2017-03-07 | International Business Machines Corporation | Merging metadata for database storage regions based on overlapping range values |
CN103605848A (en) * | 2013-11-19 | 2014-02-26 | 北京国双科技有限公司 | Method and device for analyzing paths |
US10824622B2 (en) * | 2013-11-25 | 2020-11-03 | Sap Se | Data statistics in data management systems |
US10268638B2 (en) * | 2013-11-27 | 2019-04-23 | Paraccel Llc | Limiting plan choice for database queries using plan constraints |
US10394807B2 (en) * | 2013-11-27 | 2019-08-27 | Paraccel Llc | Rewrite constraints for database queries |
EP3373134B1 (en) | 2013-12-06 | 2020-07-22 | Ab Initio Technology LLC | Source code translation |
CN104714975A (en) * | 2013-12-17 | 2015-06-17 | 航天信息股份有限公司 | Dynamic query sentence processing method and device |
US9672288B2 (en) | 2013-12-30 | 2017-06-06 | Yahoo! Inc. | Query suggestions |
US9910860B2 (en) * | 2014-02-06 | 2018-03-06 | International Business Machines Corporation | Split elimination in MapReduce systems |
US9678825B2 (en) * | 2014-02-18 | 2017-06-13 | International Business Machines Corporation | Autonomous reconfiguration of a failed user action |
US9870390B2 (en) | 2014-02-18 | 2018-01-16 | Oracle International Corporation | Selecting from OR-expansion states of a query |
US10275504B2 (en) * | 2014-02-21 | 2019-04-30 | International Business Machines Corporation | Updating database statistics with dynamic profiles |
US10108649B2 (en) * | 2014-02-25 | 2018-10-23 | Internatonal Business Machines Corporation | Early exit from table scans of loosely ordered and/or grouped relations using nearly ordered maps |
US10108622B2 (en) | 2014-03-26 | 2018-10-23 | International Business Machines Corporation | Autonomic regulation of a volatile database table attribute |
US9519687B2 (en) | 2014-06-16 | 2016-12-13 | International Business Machines Corporation | Minimizing index maintenance costs for database storage regions using hybrid zone maps and indices |
US10102480B2 (en) | 2014-06-30 | 2018-10-16 | Amazon Technologies, Inc. | Machine learning service |
US10540606B2 (en) | 2014-06-30 | 2020-01-21 | Amazon Technologies, Inc. | Consistent filtering of machine learning data |
US10318882B2 (en) | 2014-09-11 | 2019-06-11 | Amazon Technologies, Inc. | Optimized training of linear machine learning models |
US10963810B2 (en) | 2014-06-30 | 2021-03-30 | Amazon Technologies, Inc. | Efficient duplicate detection for machine learning data sets |
US11100420B2 (en) | 2014-06-30 | 2021-08-24 | Amazon Technologies, Inc. | Input processing for machine learning |
US10339465B2 (en) | 2014-06-30 | 2019-07-02 | Amazon Technologies, Inc. | Optimized decision tree based models |
US9886670B2 (en) | 2014-06-30 | 2018-02-06 | Amazon Technologies, Inc. | Feature processing recipes for machine learning |
US10169715B2 (en) | 2014-06-30 | 2019-01-01 | Amazon Technologies, Inc. | Feature processing tradeoff management |
US11182691B1 (en) | 2014-08-14 | 2021-11-23 | Amazon Technologies, Inc. | Category-based sampling of machine learning data |
US10394818B2 (en) | 2014-09-26 | 2019-08-27 | Oracle International Corporation | System and method for dynamic database split generation in a massively parallel or distributed database environment |
US10089377B2 (en) | 2014-09-26 | 2018-10-02 | Oracle International Corporation | System and method for data transfer from JDBC to a data warehouse layer in a massively parallel or distributed database environment |
US10078684B2 (en) * | 2014-09-26 | 2018-09-18 | Oracle International Corporation | System and method for query processing with table-level predicate pushdown in a massively parallel or distributed database environment |
US10380114B2 (en) | 2014-09-26 | 2019-08-13 | Oracle International Corporation | System and method for generating rowid range-based splits in a massively parallel or distributed database environment |
US10180973B2 (en) | 2014-09-26 | 2019-01-15 | Oracle International Corporation | System and method for efficient connection management in a massively parallel or distributed database environment |
US10387421B2 (en) | 2014-09-26 | 2019-08-20 | Oracle International Corporation | System and method for generating size-based splits in a massively parallel or distributed database environment |
US10089357B2 (en) | 2014-09-26 | 2018-10-02 | Oracle International Corporation | System and method for generating partition-based splits in a massively parallel or distributed database environment |
US10528596B2 (en) | 2014-09-26 | 2020-01-07 | Oracle International Corporation | System and method for consistent reads between tasks in a massively parallel or distributed database environment |
US9779117B1 (en) * | 2014-09-30 | 2017-10-03 | EMC IP Holding Company LLC | Database partitioning scheme evaluation and comparison |
CN105574031B (en) | 2014-10-16 | 2019-01-04 | 国际商业机器公司 | method and system for database index |
US10437819B2 (en) | 2014-11-14 | 2019-10-08 | Ab Initio Technology Llc | Processing queries containing a union-type operation |
US10019480B2 (en) * | 2014-11-14 | 2018-07-10 | International Business Machines Corporation | Query tuning in the cloud |
US9779133B2 (en) * | 2014-11-25 | 2017-10-03 | Sap Se | Contextual debugging of SQL queries in database-accessing applications |
US10042887B2 (en) * | 2014-12-05 | 2018-08-07 | International Business Machines Corporation | Query optimization with zone map selectivity modeling |
US10176157B2 (en) * | 2015-01-03 | 2019-01-08 | International Business Machines Corporation | Detect annotation error by segmenting unannotated document segments into smallest partition |
CN104615696B (en) * | 2015-01-23 | 2018-05-01 | 国家电网公司 | A kind of 95598 knowledge base system and building method |
US9990396B2 (en) * | 2015-02-03 | 2018-06-05 | International Business Machines Corporation | Forecasting query access plan obsolescence |
US10417281B2 (en) | 2015-02-18 | 2019-09-17 | Ab Initio Technology Llc | Querying a data source on a network |
US10817520B1 (en) * | 2015-02-25 | 2020-10-27 | EMC IP Holding Company LLC | Methods, systems, and computer readable mediums for sharing user activity data |
WO2016146057A2 (en) * | 2015-03-16 | 2016-09-22 | Huawei Technologies Co., Ltd. | A method and a plan optimizing apparatus for optimizing query execution plan |
US10585887B2 (en) | 2015-03-30 | 2020-03-10 | Oracle International Corporation | Multi-system query execution plan |
US10108664B2 (en) | 2015-04-01 | 2018-10-23 | International Business Machines Corporation | Generating multiple query access plans for multiple computing environments |
US9916353B2 (en) | 2015-04-01 | 2018-03-13 | International Business Machines Corporation | Generating multiple query access plans for multiple computing environments |
US9760591B2 (en) | 2015-05-14 | 2017-09-12 | Walleye Software, LLC | Dynamic code loading |
CN104933190B (en) * | 2015-07-10 | 2018-04-17 | 上海新炬网络信息技术股份有限公司 | A kind of SQL statement performs frequency dynamic adjusting method |
US10229358B2 (en) * | 2015-08-07 | 2019-03-12 | International Business Machines Corporation | Optimizer problem determination |
WO2017026988A1 (en) * | 2015-08-07 | 2017-02-16 | Hewlett Packard Enterprise Development Lp | Annotated query generator |
US10152509B2 (en) | 2015-09-23 | 2018-12-11 | International Business Machines Corporation | Query hint learning in a database management system |
US10216748B1 (en) | 2015-09-30 | 2019-02-26 | EMC IP Holding Company LLC | Segment index access management in a de-duplication system |
US10061801B2 (en) | 2015-10-12 | 2018-08-28 | International Business Machines Corporation | Customize column sequence in projection list of select queries |
US10599651B2 (en) | 2015-10-21 | 2020-03-24 | Oracle International Corporation | Database system feature management |
US10257275B1 (en) | 2015-10-26 | 2019-04-09 | Amazon Technologies, Inc. | Tuning software execution environments using Bayesian models |
US10055459B2 (en) | 2015-11-09 | 2018-08-21 | International Business Machines Corporation | Query hint management for a database management system |
US9971831B2 (en) * | 2015-11-25 | 2018-05-15 | International Business Machines Corporation | Managing complex queries with predicates |
WO2017097103A1 (en) * | 2015-12-11 | 2017-06-15 | Huawei Technologies Co., Ltd. | Recommendation system, apparatus and method thereof to guide self-service analytic |
CN107102995B (en) * | 2016-02-19 | 2020-02-21 | 华为技术有限公司 | Method and device for determining SQL execution plan |
CN107193813B (en) | 2016-03-14 | 2021-05-14 | 阿里巴巴集团控股有限公司 | Data table connection mode processing method and device |
US11074254B2 (en) | 2016-03-23 | 2021-07-27 | International Business Machines Corporation | Performance management using thresholds for queries of a service for a database as a service |
JP6669571B2 (en) * | 2016-04-19 | 2020-03-18 | 株式会社シスバンク | Tuning apparatus and method for relational database |
US10558458B2 (en) | 2016-06-06 | 2020-02-11 | Microsoft Technology Licensing, Llc | Query optimizer for CPU utilization and code refactoring |
US10248692B2 (en) * | 2016-06-15 | 2019-04-02 | International Business Machines Corporation | Cardinality estimation of a join predicate |
US10831750B2 (en) * | 2016-08-24 | 2020-11-10 | Nec Corporation | Security monitoring with progressive behavioral query language databases |
US10817540B2 (en) * | 2016-09-02 | 2020-10-27 | Snowflake Inc. | Incremental clustering maintenance of a table |
WO2018053024A1 (en) * | 2016-09-13 | 2018-03-22 | The Bank Of New York Mellon | Organizing datasets for adaptive responses to queries |
US10452652B2 (en) | 2016-09-15 | 2019-10-22 | At&T Intellectual Property I, L.P. | Recommendation platform for structured queries |
US11232102B2 (en) * | 2016-10-17 | 2022-01-25 | Salesforce.Com, Inc. | Background processing to provide automated database query tuning |
US11151108B2 (en) | 2016-11-21 | 2021-10-19 | International Business Machines Corporation | Indexing and archiving multiple statements using a single statement dictionary |
CN109313639B (en) * | 2016-12-06 | 2021-03-05 | 华为技术有限公司 | System and method for executing query in DBMS |
US10740332B2 (en) * | 2017-01-20 | 2020-08-11 | Futurewei Technologies, Inc. | Memory-aware plan negotiation in query concurrency control |
US10664473B2 (en) * | 2017-01-30 | 2020-05-26 | International Business Machines Corporation | Database optimization based on forecasting hardware statistics using data mining techniques |
CN107688589B (en) * | 2017-02-20 | 2019-02-26 | 平安科技(深圳)有限公司 | The method and device of Database System Optimization |
US10565214B2 (en) | 2017-03-22 | 2020-02-18 | Bank Of America Corporation | Intelligent database control systems with automated request assessments |
CN106991174A (en) * | 2017-04-05 | 2017-07-28 | 广东浪潮大数据研究有限公司 | A kind of optimization method of Smart Rack system databases |
US10242037B2 (en) | 2017-04-20 | 2019-03-26 | Servicenow, Inc. | Index suggestion engine for relational databases |
US11372858B2 (en) * | 2017-05-18 | 2022-06-28 | Oracle International Corporation | Estimated query performance |
US11157307B2 (en) * | 2017-05-24 | 2021-10-26 | International Business Machines Corporation | Count and transaction identifier based transaction processing |
US20190057133A1 (en) * | 2017-08-15 | 2019-02-21 | Salesforce.Com, Inc. | Systems and methods of bounded scans on multi-column keys of a database |
US10198469B1 (en) | 2017-08-24 | 2019-02-05 | Deephaven Data Labs Llc | Computer data system data source refreshing using an update propagation graph having a merged join listener |
US11055285B2 (en) | 2017-09-08 | 2021-07-06 | International Business Machines Corporation | Access path optimization |
US10838961B2 (en) | 2017-09-29 | 2020-11-17 | Oracle International Corporation | Prefix compression |
CN108153808A (en) * | 2017-11-22 | 2018-06-12 | 链家网(北京)科技有限公司 | Big data data warehouse data access method and device |
US11030195B2 (en) * | 2018-01-18 | 2021-06-08 | Fmr Llc | Identifying and mitigating high-risk database queries through ranked variance analysis |
US11010380B2 (en) | 2018-02-13 | 2021-05-18 | International Business Machines Corporation | Minimizing processing using an index when non-leading columns match an aggregation key |
US11080276B2 (en) * | 2018-02-23 | 2021-08-03 | Sap Se | Optimal ranges for relational query execution plans |
US10824624B2 (en) | 2018-07-12 | 2020-11-03 | Bank Of America Corporation | System for analyzing, optimizing, and remediating a proposed data query prior to query implementation |
US11068460B2 (en) | 2018-08-06 | 2021-07-20 | Oracle International Corporation | Automated real-time index management |
US11226963B2 (en) * | 2018-10-11 | 2022-01-18 | Varada Ltd. | Method and system for executing queries on indexed views |
US11182360B2 (en) * | 2019-01-14 | 2021-11-23 | Microsoft Technology Licensing, Llc | Database tuning and performance verification using cloned database |
US11470176B2 (en) * | 2019-01-29 | 2022-10-11 | Cisco Technology, Inc. | Efficient and flexible load-balancing for clusters of caches under latency constraint |
US11138266B2 (en) | 2019-02-21 | 2021-10-05 | Microsoft Technology Licensing, Llc | Leveraging query executions to improve index recommendations |
EP3719663B1 (en) * | 2019-04-03 | 2022-10-26 | Hasso-Plattner-Institut für Digital Engineering gGmbH | Iterative multi-attribute index selection for large database systems |
US11100104B2 (en) * | 2019-04-09 | 2021-08-24 | Accenture Global Solutions Limited | Query tuning utilizing optimizer hints |
US11500755B1 (en) * | 2019-05-01 | 2022-11-15 | Amazon Technologies, Inc. | Database performance degradation detection and prevention |
US11334538B2 (en) * | 2019-05-31 | 2022-05-17 | Microsoft Technology Licensing, Llc | System and method for cardinality estimation feedback loops in query processing |
US11194805B2 (en) | 2019-06-10 | 2021-12-07 | International Business Machines Corporation | Optimization of database execution planning |
US11093223B2 (en) | 2019-07-18 | 2021-08-17 | Ab Initio Technology Llc | Automatically converting a program written in a procedural programming language into a dataflow graph and related systems and methods |
US11379410B2 (en) * | 2019-09-13 | 2022-07-05 | Oracle International Corporation | Automated information lifecycle management of indexes |
US11500837B1 (en) * | 2019-12-11 | 2022-11-15 | Amazon Technologies, Inc. | Automating optimizations for items in a hierarchical data store |
US11256694B2 (en) | 2020-04-27 | 2022-02-22 | Hewlett Packard Enterprise Development Lp | Tolerance level-based tuning of query processing |
US11372885B2 (en) * | 2020-05-13 | 2022-06-28 | Sap Se | Replication of complex augmented views |
CN111898371B (en) * | 2020-07-10 | 2022-08-16 | 中国标准化研究院 | Ontology construction method and device for rational design knowledge and computer storage medium |
US20220043822A1 (en) * | 2020-08-04 | 2022-02-10 | International Business Machines Corporation | Shadow experiments for serverless multi-tenant cloud services |
US11615095B2 (en) | 2020-10-30 | 2023-03-28 | Snowflake Inc. | Automatic pruning cutoff in a database system |
CN113282574B (en) * | 2021-07-26 | 2021-10-22 | 云和恩墨(北京)信息技术有限公司 | SQL optimization-based database operation control method, system and storage medium |
US11593306B1 (en) | 2021-10-29 | 2023-02-28 | Snowflake Inc. | File defragmentation service |
US11537613B1 (en) * | 2021-10-29 | 2022-12-27 | Snowflake Inc. | Merge small file consolidation |
CN114238395A (en) * | 2022-01-06 | 2022-03-25 | 税友软件集团股份有限公司 | Database optimization method and device, electronic equipment and storage medium |
US11947938B2 (en) * | 2022-02-11 | 2024-04-02 | Bmc Software, Inc. | Application development platform |
Citations (93)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US691931A (en) * | 1901-02-15 | 1902-01-28 | Simpson S Bryan | Bookkeeper's stool. |
US5140685A (en) * | 1988-03-14 | 1992-08-18 | Unisys Corporation | Record lock processing for multiprocessing data system with majority voting |
US5260697A (en) * | 1990-11-13 | 1993-11-09 | Wang Laboratories, Inc. | Computer with separate display plane and user interface processor |
US5398183A (en) * | 1990-12-10 | 1995-03-14 | Biomedical Systems Corporation | Holter ECG report generating system |
US5408653A (en) * | 1992-04-15 | 1995-04-18 | International Business Machines Corporation | Efficient data base access using a shared electronic store in a multi-system environment with shared disks |
US5471712A (en) * | 1993-03-19 | 1995-12-05 | Kroyer; Karl K. K. | Adjustable screen for a distribution for making a sheet-formed fibrous product |
US5481712A (en) * | 1993-04-06 | 1996-01-02 | Cognex Corporation | Method and apparatus for interactively generating a computer program for machine vision analysis of an object |
US5504917A (en) * | 1986-04-14 | 1996-04-02 | National Instruments Corporation | Method and apparatus for providing picture generation and control features in a graphical data flow environment |
US5577240A (en) * | 1994-12-07 | 1996-11-19 | Xerox Corporation | Identification of stable writes in weakly consistent replicated databases while providing access to all writes in such a database |
US5634134A (en) * | 1991-06-19 | 1997-05-27 | Hitachi, Ltd. | Method and apparatus for determining character and character mode for multi-lingual keyboard based on input characters |
US5724569A (en) * | 1991-03-29 | 1998-03-03 | Bull S.A. | Apparatus for evaluating database query performance having libraries containing information for modeling the various system components of multiple systems |
US5737601A (en) * | 1993-09-24 | 1998-04-07 | Oracle Corporation | Method and apparatus for peer-to-peer data replication including handling exceptional occurrences |
US5765159A (en) * | 1994-12-29 | 1998-06-09 | International Business Machines Corporation | System and method for generating an optimized set of relational queries for fetching data from a relational database management system in response to object queries received from an object oriented environment |
US5781912A (en) * | 1996-12-19 | 1998-07-14 | Oracle Corporation | Recoverable data replication between source site and destination site without distributed transactions |
US5794227A (en) * | 1989-12-23 | 1998-08-11 | International Computers Limited | Optimization of the order in which the comparisons of the components of a boolean query expression are applied to a database record stored as a byte stream |
US5794229A (en) * | 1993-04-16 | 1998-08-11 | Sybase, Inc. | Database system with methodology for storing a database table by vertically partitioning all columns of the table |
US5806076A (en) * | 1996-10-29 | 1998-09-08 | Oracle Corporation | Tracking dependencies between transactions in a database |
US5860069A (en) * | 1997-04-11 | 1999-01-12 | Bmc Software, Inc. | Method of efficient collection of SQL performance measures |
US5870760A (en) * | 1996-12-19 | 1999-02-09 | Oracle Corporation | Dequeuing using queue batch numbers |
US5870761A (en) * | 1996-12-19 | 1999-02-09 | Oracle Corporation | Parallel queue propagation |
US5940826A (en) * | 1997-01-07 | 1999-08-17 | Unisys Corporation | Dual XPCS for disaster recovery in multi-host computer complexes |
US5963934A (en) * | 1997-06-30 | 1999-10-05 | International Business Machines Corporation | Intelligent compilation of scripting language for query processing systems |
US5963933A (en) * | 1997-06-25 | 1999-10-05 | International Business Machines Corporation | Efficient implementation of full outer join and anti-join |
US5991765A (en) * | 1997-05-06 | 1999-11-23 | Birdstep Technology As | System and method for storing and manipulating data in an information handling system |
US6052694A (en) * | 1998-03-18 | 2000-04-18 | Electronic Data Systems Corporation | Method and apparatus for logging database performance characteristics |
US6122640A (en) * | 1998-09-22 | 2000-09-19 | Platinum Technology Ip, Inc. | Method and apparatus for reorganizing an active DBMS table |
US6212514B1 (en) * | 1998-07-31 | 2001-04-03 | International Business Machines Corporation | Data base optimization method for estimating query and trigger procedure costs |
US6275818B1 (en) * | 1997-11-06 | 2001-08-14 | International Business Machines Corporation | Cost based optimization of decision support queries using transient views |
US6321218B1 (en) * | 1999-02-24 | 2001-11-20 | Oracle Corporation | Automatically determining data that is best suited for index tuning |
US6330552B1 (en) * | 1998-09-28 | 2001-12-11 | Compaq | Database query cost model optimizer |
US6349310B1 (en) * | 1999-07-06 | 2002-02-19 | Compaq Computer Corporation | Database management system and method for accessing rows in a partitioned table |
US6353818B1 (en) * | 1998-08-19 | 2002-03-05 | Ncr Corporation | Plan-per-tuple optimizing of database queries with user-defined functions |
US6356889B1 (en) * | 1998-09-30 | 2002-03-12 | International Business Machines Corporation | Method for determining optimal database materializations using a query optimizer |
US6366901B1 (en) * | 1998-12-16 | 2002-04-02 | Microsoft Corporation | Automatic database statistics maintenance and plan regeneration |
US6366903B1 (en) * | 2000-04-20 | 2002-04-02 | Microsoft Corporation | Index and materialized view selection for a given workload |
US6374257B1 (en) * | 1999-06-16 | 2002-04-16 | Oracle Corporation | Method and system for removing ambiguities in a shared database command |
US6397227B1 (en) * | 1999-07-06 | 2002-05-28 | Compaq Computer Corporation | Database management system and method for updating specified tuple fields upon transaction rollback |
US20020073086A1 (en) * | 2000-07-10 | 2002-06-13 | Nicholas Thompson | Scalable and programmable query distribution and collection in a network of queryable devices |
US6434568B1 (en) * | 1999-08-31 | 2002-08-13 | Accenture Llp | Information services patterns in a netcentric environment |
US6434545B1 (en) * | 1998-12-16 | 2002-08-13 | Microsoft Corporation | Graphical query analyzer |
US6442748B1 (en) * | 1999-08-31 | 2002-08-27 | Accenture Llp | System, method and article of manufacture for a persistent state and persistent object separator in an information services patterns environment |
US20020120617A1 (en) * | 2001-02-28 | 2002-08-29 | Fujitsu Limited | Database retrieving method, apparatus and storage medium thereof |
US6460027B1 (en) * | 1998-09-14 | 2002-10-01 | International Business Machines Corporation | Automatic recognition and rerouting of queries for optimal performance |
US6460043B1 (en) * | 1998-02-04 | 2002-10-01 | Microsoft Corporation | Method and apparatus for operating on data with a conceptual data manipulation language |
US6493701B2 (en) * | 2000-11-22 | 2002-12-10 | Sybase, Inc. | Database system with methodogy providing faster N-ary nested loop joins |
US6496850B1 (en) * | 1999-08-31 | 2002-12-17 | Accenture Llp | Clean-up of orphaned server contexts |
US20030018618A1 (en) * | 2001-03-15 | 2003-01-23 | International Business Machines Corporation | Representation for data used in query optimization |
US6513029B1 (en) * | 2000-04-20 | 2003-01-28 | Microsoft Corporation | Interesting table-subset selection for database workload materialized view selection |
US6529901B1 (en) * | 1999-06-29 | 2003-03-04 | Microsoft Corporation | Automating statistics management for query optimizers |
US20030065648A1 (en) * | 2001-10-03 | 2003-04-03 | International Business Machines Corporation | Reduce database monitor workload by employing predictive query threshold |
US6560606B1 (en) * | 1999-05-04 | 2003-05-06 | Metratech | Method and apparatus for processing data with multiple processing modules and associated counters |
US20030088541A1 (en) * | 2001-06-21 | 2003-05-08 | Zilio Daniel C. | Method for recommending indexes and materialized views for a database workload |
US6571233B2 (en) * | 2000-12-06 | 2003-05-27 | International Business Machines Corporation | Optimization of SQL queries using filtering predicates |
US20030110153A1 (en) * | 2001-12-11 | 2003-06-12 | Sprint Communications Company L.P. | Database performance monitoring method and tool |
US20030115183A1 (en) * | 2001-12-13 | 2003-06-19 | International Business Machines Corporation | Estimation and use of access plan statistics |
US20030126143A1 (en) * | 2001-06-12 | 2003-07-03 | Nicholas Roussopoulos | Dwarf cube architecture for reducing storage sizes of multidimensional data |
US6594653B2 (en) * | 1998-03-27 | 2003-07-15 | International Business Machines Corporation | Server integrated system and methods for processing precomputed views |
US20030135478A1 (en) * | 2001-05-31 | 2003-07-17 | Computer Associates Think, Inc. | Method and system for online reorganization of databases |
US6598038B1 (en) * | 1999-09-17 | 2003-07-22 | Oracle International Corporation | Workload reduction mechanism for index tuning |
US20030154216A1 (en) * | 2002-02-14 | 2003-08-14 | International Business Machines Corporation | Database optimization apparatus and method |
US6615223B1 (en) * | 2000-02-29 | 2003-09-02 | Oracle International Corporation | Method and system for data replication |
US20030182276A1 (en) * | 2002-03-19 | 2003-09-25 | International Business Machines Corporation | Method, system, and program for performance tuning a database query |
US20030187831A1 (en) * | 2002-03-29 | 2003-10-02 | International Business Machines Corporation | Database query optimizer framework with dynamic strategy dispatch |
US20030200537A1 (en) * | 2002-04-18 | 2003-10-23 | International Business Machines Corporation | Apparatus and method for using database knowledge to optimize a computer program |
US20030200204A1 (en) * | 2002-04-19 | 2003-10-23 | Limoges Joseph Serge | Substituting parameter markers for literals in database query language statement to promote reuse of previously generated access plans |
US20030229621A1 (en) * | 2002-06-07 | 2003-12-11 | International Business Machines Corporation | Apparatus and method for refreshing a database query |
US20040002957A1 (en) * | 2002-06-28 | 2004-01-01 | Microsoft Corporation | Linear programming approach to assigning benefit to database physical design structures |
US20040034643A1 (en) * | 2002-08-19 | 2004-02-19 | International Business Machines Corporation | System and method for real time statistics collection for use in the automatic management of a database system |
US6701345B1 (en) * | 2000-04-13 | 2004-03-02 | Accenture Llp | Providing a notification when a plurality of users are altering similar data in a health care solution environment |
US6714943B1 (en) * | 2001-01-31 | 2004-03-30 | Oracle International Corporation | Method and mechanism for tracking dependencies for referential integrity constrained tables |
US6721724B1 (en) * | 2000-03-31 | 2004-04-13 | Microsoft Corporation | Validating multiple execution plans for database queries |
US6728719B1 (en) * | 2001-01-31 | 2004-04-27 | Oracle International Corporation | Method and mechanism for dependency tracking for unique constraints |
US6728720B1 (en) * | 1999-07-02 | 2004-04-27 | Robert Stephen Gerard Lenzie | Identifying preferred indexes for databases |
US6763353B2 (en) * | 1998-12-07 | 2004-07-13 | Vitria Technology, Inc. | Real time business process analysis method and apparatus |
US6804672B1 (en) * | 2001-01-31 | 2004-10-12 | Oracle International Corporation | Method and mechanism for dependency tracking |
US20040210563A1 (en) * | 2003-04-21 | 2004-10-21 | Oracle International Corporation | Method and system of collecting execution statistics of query statements |
US6816874B1 (en) * | 1999-09-10 | 2004-11-09 | International Business Machines Corporation | Method, system, and program for accessing performance data |
US6839713B1 (en) * | 2001-07-12 | 2005-01-04 | Advanced Micro Devices, Inc. | System and software for database structure in semiconductor manufacturing and method thereof |
US6850925B2 (en) * | 2001-05-15 | 2005-02-01 | Microsoft Corporation | Query optimization by sub-plan memoization |
US20050033734A1 (en) * | 2003-08-05 | 2005-02-10 | International Business Machines Corporation | Performance prediction system with query mining |
US6865567B1 (en) * | 1999-07-30 | 2005-03-08 | Basantkumar John Oommen | Method of generating attribute cardinality maps |
US20050097078A1 (en) * | 2003-10-31 | 2005-05-05 | Lohman Guy M. | System, method, and computer program product for progressive query processing |
US20050102305A1 (en) * | 2002-06-26 | 2005-05-12 | Microsoft Corporation | Compressing database workloads |
US6910109B2 (en) * | 1998-09-30 | 2005-06-21 | Intel Corporation | Tracking memory page state |
US6915290B2 (en) * | 2001-12-11 | 2005-07-05 | International Business Machines Corporation | Database query optimization apparatus and method that represents queries as graphs |
US6931389B1 (en) * | 1997-10-14 | 2005-08-16 | International Business Machines Corporation | System and method for filtering query statements from multiple plans and packages according to user-defined filters of query explain data |
US6934701B1 (en) * | 2000-01-04 | 2005-08-23 | International Business Machines Corporation | Using a stored procedure to access index configuration data in a remote database management system |
US6947927B2 (en) * | 2002-07-09 | 2005-09-20 | Microsoft Corporation | Method and apparatus for exploiting statistics on query expressions for optimization |
US6961931B2 (en) * | 2001-01-10 | 2005-11-01 | International Business Machines Corporation | Dependency specification using target patterns |
US6999958B2 (en) * | 2002-06-07 | 2006-02-14 | International Business Machines Corporation | Runtime query optimization for dynamically selecting from multiple plans in a query based upon runtime-evaluated performance criterion |
US7007013B2 (en) * | 2002-07-26 | 2006-02-28 | International Business Machines Corporation | Fast computation of spatial queries in location-based services |
US7031958B2 (en) * | 2003-02-06 | 2006-04-18 | International Business Machines Corporation | Patterned based query optimization |
US7080062B1 (en) * | 1999-05-18 | 2006-07-18 | International Business Machines Corporation | Optimizing database queries using query execution plans derived from automatic summary table determining cost based queries |
Family Cites Families (29)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5794228A (en) * | 1993-04-16 | 1998-08-11 | Sybase, Inc. | Database system with buffer manager providing per page native data compression and decompression |
US5544355A (en) * | 1993-06-14 | 1996-08-06 | Hewlett-Packard Company | Method and apparatus for query optimization in a relational database system having foreign functions |
US6195653B1 (en) * | 1997-10-14 | 2001-02-27 | International Business Machines Corporation | System and method for selectively preparing customized reports of query explain data |
US6813617B2 (en) * | 1998-10-05 | 2004-11-02 | Oracle International Corporation | Dynamic generation of optimizer hints |
US6496819B1 (en) * | 1998-12-28 | 2002-12-17 | Oracle Corporation | Rewriting a query in terms of a summary based on functional dependencies and join backs, and based on join derivability |
US6334128B1 (en) * | 1998-12-28 | 2001-12-25 | Oracle Corporation | Method and apparatus for efficiently refreshing sets of summary tables and materialized views in a database management system |
US7890491B1 (en) * | 1999-12-22 | 2011-02-15 | International Business Machines Corporation | Query optimization technique for obtaining improved cardinality estimates using statistics on automatic summary tables |
US6266658B1 (en) * | 2000-04-20 | 2001-07-24 | Microsoft Corporation | Index tuner for given workload |
WO2001093105A2 (en) * | 2000-05-26 | 2001-12-06 | Computer Associates Think, Inc. | System and method for automatically generating database queries |
US7272589B1 (en) | 2000-11-01 | 2007-09-18 | Oracle International Corporation | Database index validation mechanism |
US6763359B2 (en) * | 2001-06-06 | 2004-07-13 | International Business Machines Corporation | Learning from empirical results in query optimization |
US7617201B1 (en) * | 2001-06-20 | 2009-11-10 | Microstrategy, Incorporated | System and method for analyzing statistics in a reporting system |
US7155426B2 (en) * | 2001-09-20 | 2006-12-26 | International Business Machines Corporation | SQL debugging using stored procedures |
US7499907B2 (en) * | 2001-10-12 | 2009-03-03 | Teradata Us, Inc. | Index selection in a database system |
US7523142B2 (en) | 2001-12-17 | 2009-04-21 | Sap Ag | Systems, methods and articles of manufacture for upgrading a database with a shadow system |
US7058622B1 (en) | 2001-12-26 | 2006-06-06 | Tedesco Michael A | Method, apparatus and system for screening database queries prior to submission to a database |
US7047231B2 (en) * | 2002-03-01 | 2006-05-16 | Software Engineering Gmbh | Getpage-workload based index optimizer |
US7155459B2 (en) * | 2002-06-28 | 2006-12-26 | Miccrosoft Corporation | Time-bound database tuning |
US20040019587A1 (en) | 2002-07-25 | 2004-01-29 | You-Chin Fuh | Method and device for processing a query in a database management system |
JP2004110219A (en) * | 2002-09-17 | 2004-04-08 | Hitachi Ltd | Data processing system and join processing method |
WO2004036344A2 (en) | 2002-10-15 | 2004-04-29 | Active-Base Ltd. | System and method for the optimization of database |
US7895191B2 (en) * | 2003-04-09 | 2011-02-22 | International Business Machines Corporation | Improving performance of database queries |
US7146363B2 (en) | 2003-05-20 | 2006-12-05 | Microsoft Corporation | System and method for cardinality estimation based on query execution feedback |
US7174328B2 (en) * | 2003-09-02 | 2007-02-06 | International Business Machines Corp. | Selective path signatures for query processing over a hierarchical tagged data structure |
US7805411B2 (en) | 2003-09-06 | 2010-09-28 | Oracle International Corporation | Auto-tuning SQL statements |
US7302422B2 (en) * | 2004-04-14 | 2007-11-27 | International Business Machines Corporation | Query workload statistics collection in a database management system |
US20050251523A1 (en) | 2004-05-07 | 2005-11-10 | Oracle International Corporation | Minimizing downtime for application changes in database systems |
US7788285B2 (en) | 2004-05-14 | 2010-08-31 | Oracle International Corporation | Finer grain dependency tracking for database objects |
US7353219B2 (en) | 2004-05-28 | 2008-04-01 | International Business Machines Corporation | Determining validity ranges of query plans based on suboptimality |
-
2004
- 2004-09-07 US US10/935,908 patent/US7805411B2/en active Active
- 2004-09-07 US US10/936,778 patent/US7747606B2/en active Active
- 2004-09-07 US US10/935,906 patent/US20050119999A1/en not_active Abandoned
- 2004-09-07 US US10/936,781 patent/US7739263B2/en active Active
- 2004-09-07 US US10/936,469 patent/US8825629B2/en active Active
- 2004-09-07 US US10/936,468 patent/US8983934B2/en active Active
- 2004-09-07 US US10/936,426 patent/US7634456B2/en active Active
- 2004-09-07 US US10/936,205 patent/US7664730B2/en active Active
- 2004-09-07 US US10/936,427 patent/US20050138015A1/en not_active Abandoned
- 2004-09-07 US US10/936,449 patent/US7664778B2/en active Active
- 2004-09-07 US US10/936,779 patent/US20050177557A1/en not_active Abandoned
Patent Citations (98)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US691931A (en) * | 1901-02-15 | 1902-01-28 | Simpson S Bryan | Bookkeeper's stool. |
US5504917A (en) * | 1986-04-14 | 1996-04-02 | National Instruments Corporation | Method and apparatus for providing picture generation and control features in a graphical data flow environment |
US5140685A (en) * | 1988-03-14 | 1992-08-18 | Unisys Corporation | Record lock processing for multiprocessing data system with majority voting |
US5794227A (en) * | 1989-12-23 | 1998-08-11 | International Computers Limited | Optimization of the order in which the comparisons of the components of a boolean query expression are applied to a database record stored as a byte stream |
US5260697A (en) * | 1990-11-13 | 1993-11-09 | Wang Laboratories, Inc. | Computer with separate display plane and user interface processor |
US5398183A (en) * | 1990-12-10 | 1995-03-14 | Biomedical Systems Corporation | Holter ECG report generating system |
US5724569A (en) * | 1991-03-29 | 1998-03-03 | Bull S.A. | Apparatus for evaluating database query performance having libraries containing information for modeling the various system components of multiple systems |
US5634134A (en) * | 1991-06-19 | 1997-05-27 | Hitachi, Ltd. | Method and apparatus for determining character and character mode for multi-lingual keyboard based on input characters |
US5408653A (en) * | 1992-04-15 | 1995-04-18 | International Business Machines Corporation | Efficient data base access using a shared electronic store in a multi-system environment with shared disks |
US5761660A (en) * | 1992-04-15 | 1998-06-02 | International Business Machines Corporation | Computer program product and program storage device for database access using a shared electronic store in a multi-system environment having shared disks |
US5471712A (en) * | 1993-03-19 | 1995-12-05 | Kroyer; Karl K. K. | Adjustable screen for a distribution for making a sheet-formed fibrous product |
US5481712A (en) * | 1993-04-06 | 1996-01-02 | Cognex Corporation | Method and apparatus for interactively generating a computer program for machine vision analysis of an object |
US5794229A (en) * | 1993-04-16 | 1998-08-11 | Sybase, Inc. | Database system with methodology for storing a database table by vertically partitioning all columns of the table |
US5737601A (en) * | 1993-09-24 | 1998-04-07 | Oracle Corporation | Method and apparatus for peer-to-peer data replication including handling exceptional occurrences |
US5577240A (en) * | 1994-12-07 | 1996-11-19 | Xerox Corporation | Identification of stable writes in weakly consistent replicated databases while providing access to all writes in such a database |
US5765159A (en) * | 1994-12-29 | 1998-06-09 | International Business Machines Corporation | System and method for generating an optimized set of relational queries for fetching data from a relational database management system in response to object queries received from an object oriented environment |
US5806076A (en) * | 1996-10-29 | 1998-09-08 | Oracle Corporation | Tracking dependencies between transactions in a database |
US5781912A (en) * | 1996-12-19 | 1998-07-14 | Oracle Corporation | Recoverable data replication between source site and destination site without distributed transactions |
US5870760A (en) * | 1996-12-19 | 1999-02-09 | Oracle Corporation | Dequeuing using queue batch numbers |
US5870761A (en) * | 1996-12-19 | 1999-02-09 | Oracle Corporation | Parallel queue propagation |
US5940826A (en) * | 1997-01-07 | 1999-08-17 | Unisys Corporation | Dual XPCS for disaster recovery in multi-host computer complexes |
US5860069A (en) * | 1997-04-11 | 1999-01-12 | Bmc Software, Inc. | Method of efficient collection of SQL performance measures |
US5991765A (en) * | 1997-05-06 | 1999-11-23 | Birdstep Technology As | System and method for storing and manipulating data in an information handling system |
US5963933A (en) * | 1997-06-25 | 1999-10-05 | International Business Machines Corporation | Efficient implementation of full outer join and anti-join |
US5963934A (en) * | 1997-06-30 | 1999-10-05 | International Business Machines Corporation | Intelligent compilation of scripting language for query processing systems |
US6931389B1 (en) * | 1997-10-14 | 2005-08-16 | International Business Machines Corporation | System and method for filtering query statements from multiple plans and packages according to user-defined filters of query explain data |
US6275818B1 (en) * | 1997-11-06 | 2001-08-14 | International Business Machines Corporation | Cost based optimization of decision support queries using transient views |
US6460043B1 (en) * | 1998-02-04 | 2002-10-01 | Microsoft Corporation | Method and apparatus for operating on data with a conceptual data manipulation language |
US6052694A (en) * | 1998-03-18 | 2000-04-18 | Electronic Data Systems Corporation | Method and apparatus for logging database performance characteristics |
US6594653B2 (en) * | 1998-03-27 | 2003-07-15 | International Business Machines Corporation | Server integrated system and methods for processing precomputed views |
US6212514B1 (en) * | 1998-07-31 | 2001-04-03 | International Business Machines Corporation | Data base optimization method for estimating query and trigger procedure costs |
US6353818B1 (en) * | 1998-08-19 | 2002-03-05 | Ncr Corporation | Plan-per-tuple optimizing of database queries with user-defined functions |
US6460027B1 (en) * | 1998-09-14 | 2002-10-01 | International Business Machines Corporation | Automatic recognition and rerouting of queries for optimal performance |
US6122640A (en) * | 1998-09-22 | 2000-09-19 | Platinum Technology Ip, Inc. | Method and apparatus for reorganizing an active DBMS table |
US6330552B1 (en) * | 1998-09-28 | 2001-12-11 | Compaq | Database query cost model optimizer |
US6910109B2 (en) * | 1998-09-30 | 2005-06-21 | Intel Corporation | Tracking memory page state |
US6356889B1 (en) * | 1998-09-30 | 2002-03-12 | International Business Machines Corporation | Method for determining optimal database materializations using a query optimizer |
US6763353B2 (en) * | 1998-12-07 | 2004-07-13 | Vitria Technology, Inc. | Real time business process analysis method and apparatus |
US20030177137A1 (en) * | 1998-12-16 | 2003-09-18 | Microsoft Corporation | Graphical query analyzer |
US6434545B1 (en) * | 1998-12-16 | 2002-08-13 | Microsoft Corporation | Graphical query analyzer |
US6744449B2 (en) * | 1998-12-16 | 2004-06-01 | Microsoft Corporation | Graphical query analyzer |
US6366901B1 (en) * | 1998-12-16 | 2002-04-02 | Microsoft Corporation | Automatic database statistics maintenance and plan regeneration |
US6321218B1 (en) * | 1999-02-24 | 2001-11-20 | Oracle Corporation | Automatically determining data that is best suited for index tuning |
US6560606B1 (en) * | 1999-05-04 | 2003-05-06 | Metratech | Method and apparatus for processing data with multiple processing modules and associated counters |
US7080062B1 (en) * | 1999-05-18 | 2006-07-18 | International Business Machines Corporation | Optimizing database queries using query execution plans derived from automatic summary table determining cost based queries |
US6374257B1 (en) * | 1999-06-16 | 2002-04-16 | Oracle Corporation | Method and system for removing ambiguities in a shared database command |
US6529901B1 (en) * | 1999-06-29 | 2003-03-04 | Microsoft Corporation | Automating statistics management for query optimizers |
US6728720B1 (en) * | 1999-07-02 | 2004-04-27 | Robert Stephen Gerard Lenzie | Identifying preferred indexes for databases |
US6349310B1 (en) * | 1999-07-06 | 2002-02-19 | Compaq Computer Corporation | Database management system and method for accessing rows in a partitioned table |
US6397227B1 (en) * | 1999-07-06 | 2002-05-28 | Compaq Computer Corporation | Database management system and method for updating specified tuple fields upon transaction rollback |
US6865567B1 (en) * | 1999-07-30 | 2005-03-08 | Basantkumar John Oommen | Method of generating attribute cardinality maps |
US6496850B1 (en) * | 1999-08-31 | 2002-12-17 | Accenture Llp | Clean-up of orphaned server contexts |
US6442748B1 (en) * | 1999-08-31 | 2002-08-27 | Accenture Llp | System, method and article of manufacture for a persistent state and persistent object separator in an information services patterns environment |
US6434568B1 (en) * | 1999-08-31 | 2002-08-13 | Accenture Llp | Information services patterns in a netcentric environment |
US6816874B1 (en) * | 1999-09-10 | 2004-11-09 | International Business Machines Corporation | Method, system, and program for accessing performance data |
US6598038B1 (en) * | 1999-09-17 | 2003-07-22 | Oracle International Corporation | Workload reduction mechanism for index tuning |
US6934701B1 (en) * | 2000-01-04 | 2005-08-23 | International Business Machines Corporation | Using a stored procedure to access index configuration data in a remote database management system |
US6615223B1 (en) * | 2000-02-29 | 2003-09-02 | Oracle International Corporation | Method and system for data replication |
US6721724B1 (en) * | 2000-03-31 | 2004-04-13 | Microsoft Corporation | Validating multiple execution plans for database queries |
US6701345B1 (en) * | 2000-04-13 | 2004-03-02 | Accenture Llp | Providing a notification when a plurality of users are altering similar data in a health care solution environment |
US6513029B1 (en) * | 2000-04-20 | 2003-01-28 | Microsoft Corporation | Interesting table-subset selection for database workload materialized view selection |
US6366903B1 (en) * | 2000-04-20 | 2002-04-02 | Microsoft Corporation | Index and materialized view selection for a given workload |
US20020073086A1 (en) * | 2000-07-10 | 2002-06-13 | Nicholas Thompson | Scalable and programmable query distribution and collection in a network of queryable devices |
US6493701B2 (en) * | 2000-11-22 | 2002-12-10 | Sybase, Inc. | Database system with methodogy providing faster N-ary nested loop joins |
US6571233B2 (en) * | 2000-12-06 | 2003-05-27 | International Business Machines Corporation | Optimization of SQL queries using filtering predicates |
US6961931B2 (en) * | 2001-01-10 | 2005-11-01 | International Business Machines Corporation | Dependency specification using target patterns |
US6714943B1 (en) * | 2001-01-31 | 2004-03-30 | Oracle International Corporation | Method and mechanism for tracking dependencies for referential integrity constrained tables |
US6728719B1 (en) * | 2001-01-31 | 2004-04-27 | Oracle International Corporation | Method and mechanism for dependency tracking for unique constraints |
US6804672B1 (en) * | 2001-01-31 | 2004-10-12 | Oracle International Corporation | Method and mechanism for dependency tracking |
US20020120617A1 (en) * | 2001-02-28 | 2002-08-29 | Fujitsu Limited | Database retrieving method, apparatus and storage medium thereof |
US20030018618A1 (en) * | 2001-03-15 | 2003-01-23 | International Business Machines Corporation | Representation for data used in query optimization |
US6850925B2 (en) * | 2001-05-15 | 2005-02-01 | Microsoft Corporation | Query optimization by sub-plan memoization |
US20030135478A1 (en) * | 2001-05-31 | 2003-07-17 | Computer Associates Think, Inc. | Method and system for online reorganization of databases |
US20030126143A1 (en) * | 2001-06-12 | 2003-07-03 | Nicholas Roussopoulos | Dwarf cube architecture for reducing storage sizes of multidimensional data |
US20030088541A1 (en) * | 2001-06-21 | 2003-05-08 | Zilio Daniel C. | Method for recommending indexes and materialized views for a database workload |
US6839713B1 (en) * | 2001-07-12 | 2005-01-04 | Advanced Micro Devices, Inc. | System and software for database structure in semiconductor manufacturing and method thereof |
US20030065648A1 (en) * | 2001-10-03 | 2003-04-03 | International Business Machines Corporation | Reduce database monitor workload by employing predictive query threshold |
US6915290B2 (en) * | 2001-12-11 | 2005-07-05 | International Business Machines Corporation | Database query optimization apparatus and method that represents queries as graphs |
US20030110153A1 (en) * | 2001-12-11 | 2003-06-12 | Sprint Communications Company L.P. | Database performance monitoring method and tool |
US20030115183A1 (en) * | 2001-12-13 | 2003-06-19 | International Business Machines Corporation | Estimation and use of access plan statistics |
US20030154216A1 (en) * | 2002-02-14 | 2003-08-14 | International Business Machines Corporation | Database optimization apparatus and method |
US7139749B2 (en) * | 2002-03-19 | 2006-11-21 | International Business Machines Corporation | Method, system, and program for performance tuning a database query |
US20030182276A1 (en) * | 2002-03-19 | 2003-09-25 | International Business Machines Corporation | Method, system, and program for performance tuning a database query |
US20030187831A1 (en) * | 2002-03-29 | 2003-10-02 | International Business Machines Corporation | Database query optimizer framework with dynamic strategy dispatch |
US20030200537A1 (en) * | 2002-04-18 | 2003-10-23 | International Business Machines Corporation | Apparatus and method for using database knowledge to optimize a computer program |
US20030200204A1 (en) * | 2002-04-19 | 2003-10-23 | Limoges Joseph Serge | Substituting parameter markers for literals in database query language statement to promote reuse of previously generated access plans |
US6999958B2 (en) * | 2002-06-07 | 2006-02-14 | International Business Machines Corporation | Runtime query optimization for dynamically selecting from multiple plans in a query based upon runtime-evaluated performance criterion |
US20030229621A1 (en) * | 2002-06-07 | 2003-12-11 | International Business Machines Corporation | Apparatus and method for refreshing a database query |
US6912547B2 (en) * | 2002-06-26 | 2005-06-28 | Microsoft Corporation | Compressing database workloads |
US20050102305A1 (en) * | 2002-06-26 | 2005-05-12 | Microsoft Corporation | Compressing database workloads |
US20040002957A1 (en) * | 2002-06-28 | 2004-01-01 | Microsoft Corporation | Linear programming approach to assigning benefit to database physical design structures |
US6947927B2 (en) * | 2002-07-09 | 2005-09-20 | Microsoft Corporation | Method and apparatus for exploiting statistics on query expressions for optimization |
US7007013B2 (en) * | 2002-07-26 | 2006-02-28 | International Business Machines Corporation | Fast computation of spatial queries in location-based services |
US20040034643A1 (en) * | 2002-08-19 | 2004-02-19 | International Business Machines Corporation | System and method for real time statistics collection for use in the automatic management of a database system |
US7031958B2 (en) * | 2003-02-06 | 2006-04-18 | International Business Machines Corporation | Patterned based query optimization |
US20040210563A1 (en) * | 2003-04-21 | 2004-10-21 | Oracle International Corporation | Method and system of collecting execution statistics of query statements |
US20050033734A1 (en) * | 2003-08-05 | 2005-02-10 | International Business Machines Corporation | Performance prediction system with query mining |
US20050097078A1 (en) * | 2003-10-31 | 2005-05-05 | Lohman Guy M. | System, method, and computer program product for progressive query processing |
Cited By (49)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7664778B2 (en) | 2003-09-06 | 2010-02-16 | Oracle International Corporation | SQL tuning sets |
US20050177557A1 (en) * | 2003-09-06 | 2005-08-11 | Oracle International Corporation | Automatic prevention of run-away query execution |
US8825629B2 (en) | 2003-09-06 | 2014-09-02 | Oracle International Corporation | Method for index tuning of a SQL statement, and index merging for a multi-statement SQL workload, using a cost-based relational query optimizer |
US7805411B2 (en) | 2003-09-06 | 2010-09-28 | Oracle International Corporation | Auto-tuning SQL statements |
US7739263B2 (en) | 2003-09-06 | 2010-06-15 | Oracle International Corporation | Global hints |
US8983934B2 (en) | 2003-09-06 | 2015-03-17 | Oracle International Corporation | SQL tuning base |
US7664730B2 (en) | 2003-09-06 | 2010-02-16 | Oracle International Corporation | Method and system for implementing a SQL profile |
US20050119999A1 (en) * | 2003-09-06 | 2005-06-02 | Oracle International Corporation | Automatic learning optimizer |
US7984024B2 (en) | 2004-01-07 | 2011-07-19 | International Business Machines Corporation | Statistics management |
US20090030875A1 (en) * | 2004-01-07 | 2009-01-29 | International Business Machines Corporation | Statistics management |
US20050210461A1 (en) * | 2004-03-17 | 2005-09-22 | Oracle International Corporation | Method and mechanism for performing a rolling upgrade of distributed computer software |
US7757226B2 (en) | 2004-03-17 | 2010-07-13 | Oracle International Corporation | Method and mechanism for performing a rolling upgrade of distributed computer software |
US7788285B2 (en) | 2004-05-14 | 2010-08-31 | Oracle International Corporation | Finer grain dependency tracking for database objects |
US7574424B2 (en) * | 2004-10-13 | 2009-08-11 | Sybase, Inc. | Database system with methodology for parallel schedule generation in a query optimizer |
US20060080285A1 (en) * | 2004-10-13 | 2006-04-13 | Sybase, Inc. | Database System with Methodology for Parallel Schedule Generation in a Query Optimizer |
US20080133454A1 (en) * | 2004-10-29 | 2008-06-05 | International Business Machines Corporation | System and method for updating database statistics according to query feedback |
US7831592B2 (en) * | 2004-10-29 | 2010-11-09 | International Business Machines Corporation | System and method for updating database statistics according to query feedback |
US20060149695A1 (en) * | 2004-12-30 | 2006-07-06 | International Business Machines Corporation | Management of database statistics |
US7814072B2 (en) * | 2004-12-30 | 2010-10-12 | International Business Machines Corporation | Management of database statistics |
US7610264B2 (en) | 2005-02-28 | 2009-10-27 | International Business Machines Corporation | Method and system for providing a learning optimizer for federated database systems |
US20060195416A1 (en) * | 2005-02-28 | 2006-08-31 | Ewen Stephan E | Method and system for providing a learning optimizer for federated database systems |
US20060230016A1 (en) * | 2005-03-29 | 2006-10-12 | Microsoft Corporation | Systems and methods for statistics over complex objects |
US20080126393A1 (en) * | 2006-11-29 | 2008-05-29 | Bossman Patrick D | Computer program product and system for annotating a problem sql statement for improved understanding |
US20090018992A1 (en) * | 2007-07-12 | 2009-01-15 | Ibm Corporation | Management of interesting database statistics |
US8812481B2 (en) * | 2007-07-12 | 2014-08-19 | International Business Machines Corporation | Management of interesting database statistics |
US20090077016A1 (en) * | 2007-09-14 | 2009-03-19 | Oracle International Corporation | Fully automated sql tuning |
US9734200B2 (en) | 2007-09-14 | 2017-08-15 | Oracle International Corporation | Identifying high risk database statements in changing database environments |
US8903801B2 (en) * | 2007-09-14 | 2014-12-02 | Oracle International Corporation | Fully automated SQL tuning |
US9720941B2 (en) | 2007-09-14 | 2017-08-01 | Oracle International Corporation | Fully automated SQL tuning |
US20090106306A1 (en) * | 2007-10-17 | 2009-04-23 | Dinesh Das | SQL Execution Plan Baselines |
US9189522B2 (en) | 2007-10-17 | 2015-11-17 | Oracle International Corporation | SQL execution plan baselines |
US10229158B2 (en) | 2007-10-17 | 2019-03-12 | Oracle International Corporation | SQL execution plan verification |
US20090106219A1 (en) * | 2007-10-17 | 2009-04-23 | Peter Belknap | SQL Execution Plan Verification |
US8700608B2 (en) | 2007-10-17 | 2014-04-15 | Oracle International Corporation | SQL execution plan verification |
US8577871B2 (en) | 2008-03-31 | 2013-11-05 | Oracle International Corporation | Method and mechanism for out-of-the-box real-time SQL monitoring |
US20090248621A1 (en) * | 2008-03-31 | 2009-10-01 | Benoit Dageville | Method and mechanism for out-of-the-box real-time sql monitoring |
US20090265329A1 (en) * | 2008-04-17 | 2009-10-22 | International Business Machines Corporation | System and method of data caching for compliance storage systems with keyword query based access |
US8140538B2 (en) | 2008-04-17 | 2012-03-20 | International Business Machines Corporation | System and method of data caching for compliance storage systems with keyword query based access |
US8903805B2 (en) | 2010-08-20 | 2014-12-02 | Oracle International Corporation | Method and system for performing query optimization using a hybrid execution plan |
US20150242464A1 (en) * | 2014-02-24 | 2015-08-27 | Red Hat, Inc. | Source query caching as fault prevention for federated queries |
US10114874B2 (en) * | 2014-02-24 | 2018-10-30 | Red Hat, Inc. | Source query caching as fault prevention for federated queries |
US10621064B2 (en) | 2014-07-07 | 2020-04-14 | Oracle International Corporation | Proactive impact measurement of database changes on production systems |
US10409701B2 (en) * | 2016-08-11 | 2019-09-10 | Salesforce.Com, Inc. | Per-statement monitoring in a database environment |
US11281770B2 (en) | 2016-08-11 | 2022-03-22 | Salesforce.Com, Inc. | Detection of structured query language (SQL) injection events using simple statistical analysis |
US11354306B2 (en) | 2016-08-11 | 2022-06-07 | safesforce.com, inc. | Per-statement monitoring in a database environment |
US11386058B2 (en) | 2017-09-29 | 2022-07-12 | Oracle International Corporation | Rule-based autonomous database cloud service framework |
US11327932B2 (en) | 2017-09-30 | 2022-05-10 | Oracle International Corporation | Autonomous multitenant database cloud service framework |
US20230065855A1 (en) * | 2021-08-26 | 2023-03-02 | International Business Machines Corporation | Dynamical database system resource balance |
US11748352B2 (en) * | 2021-08-26 | 2023-09-05 | International Business Machines Corporation | Dynamical database system resource balance |
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US20050125427A1 (en) | 2005-06-09 |
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US8825629B2 (en) | 2014-09-02 |
US20050125393A1 (en) | 2005-06-09 |
US7634456B2 (en) | 2009-12-15 |
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