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Oracle Database 21cNew Performance Features

Randolf Eberle-Geist

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oracle-performance.de

• Independent consultant

• Performance Troubleshooting

• In-house workshops

• Cost-Based Optimizer

• Performance By Design

• Oracle ACE Director Alumni

• Member of OakTable Network

Oracle Database 21c New Performance Features2

2009-2016 Alumni

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Agenda

• 21c new performance features

• Previous versions noticeable performance features

Oracle Database 21c New Performance Features3

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21c New Performance Features

• SQL Macros (partially backported to 19c! (>= 19.6))

• Dynamic Sequence Cache (backported to 19c! (>= 19.10))

• Automatic SQL Tuning Set (ASTS) (backported to 19c! (>= 19.7))

• Automatic Zonemaps / Materialized Views (Exadata only)

=> Object Activity Tracking System (OATS)

• In Memory / Hash Join improvements

• Persistence Memory (PMEM) support

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Previous versions noticeable performance features (1)

• Parallel Execution enhancements

• Attribute Clustering / Zonemaps (Zonemaps Exadata only)

• Database statistics enhancements (partially Exadata only)

• Approximate query / Top N processing

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Previous versions noticeable performance features (2)

• PRAGMA UDF for PL/SQL functions called from SQL

• New built-in “always on” Index usage monitoring

• Private temporary tables

• Scalable Sequences

• Memoptimized read and write rowstore (Exadata only)

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Previous versions noticeable performance features (3)

• Bitmap based COUNT(DISTINCT)

• SQL Quarantine (Exadata Only)

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SQL Macros

• Advanced text replacement logic at parse time

• PL/SQL logic evaluated at parse time, returned string replaces macro expression in SQL and the resulting SQL string is parsed / evaluated by optimizer

• No execution of PL/SQL at runtime!

• Basic idea is reusability and encapsulation similar to PL/SQL functions but without the overhead and performance / optimizer implications

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SQL Macros

• Two flavours: SCALAR (21c only) and TABLE (backported to 19c)

• TABLE Macros can only be used in the FROM clause

• SCALAR Macros everywhere else (projection, selection)

• Always defined as functions (with optional parameters) that return a string that will be put into the SQL in place of the SQL Macro

• The string returned can contain some replacement logic / “magic” based on the parameters passed into the SQL Macro

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SQL Macros

DEMO!

Oracle Database 21c New Performance Features10

21c New Performance Features Scalar SQL Macros Demo.sql21c New Performance Features Table SQL Macros Demo.sql

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SQL Macros

• Basic promise is kept: Encapsulation and reusability without sacrifyingperformance – full visibility to optimizer

• Complex scenarios possible, in particular for TABLE SQL Macros using polymorphism

• But some noticeable limitations / counterintuitive behaviour in current releases

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Dynamic Sequence Cache

• Any sequence defined with a CACHE size > 0 will get its cache size automatically dynamically resized at runtime if Oracle recognizes frequent usage of the sequence

• The CACHE_SIZE setting of the sequence isn’t updated

• The dynamic resize at runtime will adapt to the sequence usage

• It looks like sequences defined as NOCACHE don’t benefit from the feature

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Dynamic Sequence Cache

DEMO!

Oracle Database 21c New Performance Features13

dynamic_sequence_cache_demo.sqldynamic_sequence_cache_demo2.sql

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Dynamic Sequence Cache

https://docs.oracle.com/en/database/oracle/oracle-database/21/nfcon/sequence-dynamic-cache-resizing-336399199.html

https://docs.oracle.com/en/database/oracle/oracle-database/21/admin/managing-views-sequences-and-synonyms.html#GUID-83FA2D7D-6119-4182-94EA-60554024A2CE

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Automatic SQL Tuning Set (ASTS) 19.7+

• Introduced in RU 19.7 as backport, enabled by default

• Starting with RU 19.8 disabled by default

• Collects *all* plans for *all* queries seen – in contrast to AWR not only the top n “relevant” ones

• Automatic Indexing relies on it

• The idea is that plan regressions can be tackled more efficiently by identifying previously used good plans in the ASTS – automatic SQL plan management can do this automatically. With ASTS deactivated AWR might miss good executions that are not “relevant” enough during “good” times

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Automatic SQL Tuning Set (ASTS) 19.7+-- View captured SQL statementsSelect sql_textfrom dba_sqlset_Statementswhere sqlset_name = 'SYS_AUTO_STS';

-- Enable / disable taskBegin

DBMS_Auto_Task_Admin.Enable(Client_Name => 'Auto STS Capture Task',Operation => NULL,Window_name => NULL);

End;/

BeginDBMS_Auto_Task_Admin.Disable(

Client_Name => 'Auto STS Capture Task',Operation => NULL,Window_name => NULL);

End;/

-- View task statusSelect Task_Name, EnabledFrom DBA_AutoTask_Schedule_ControlWhere Task_Name = 'Auto STS Capture Task';

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Automatic SQL Tuning Set (ASTS) 19.7+

DEMO!

Oracle Database 21c New Performance Features17

automatic_sql_tuning_set_asts_demo.sql

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Parallel Execution Enhancements

• Various smaller enhancements since Oracle 12c

• Most of them aim for improving data distribution among Parallel Execution Servers: Hybrid hash / broadcast distribution (12c), Automatic skew handling (12c), Parallel Filter evaluation (12c) Null Random (18c), Adaptive PX BLOCK ITERATOR (19c)

• But the biggest threat still comes from additional BUFFEREDoperations in Parallel Execution plans due to internal implementation limitations

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Parallel Execution Enhancements

• Either these are separate, additional BUFFER SORT operations

• Or the “famous” HASH JOIN BUFFERED – which means this operation has to “buffer” all surviving rows of the second row source to join –which is the (hopefully) larger one, and hence could mean significant additional work

• Oracle 18c has introduced the new “shared” HASH JOIN

• But even in 21c it’s not yet production ready

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Parallel Execution Enhancements

• HASH JOIN SHARED is based on the new MGA (“Managed Global Area”) concept – a dynamically allocated, shared memory for a specific purpose and duration, in principle like “shared” PGA memory

• The Parallel Execution Server built each their hash table in MGA

• All Parallel Execution Servers share the “global” hash table during the probe phase

• Side effect: No specific re-distribution of data required!

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Parallel Execution Enhancements

• SHARED HASH JOIN improves the Parallel Hash Join in two ways:

• No re-distribution overhead

• No need for HASH JOIN BUFFERED

• Should give many users of Parallel Execution a significant performance boost!

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Parallel Execution Enhancements

DEMO!

Oracle Database 21c New Performance Features22

21c New Performance Features Parallel Execution enhancements.sql

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Parallel Execution Enhancements

https://chinaraliyev.wordpress.com/2019/04/29/parallel-shared-hash-join/

MGA (Managed Global Area) Reference Note (Doc ID 2638904.1)

Sizing the PGA in Oracle 19c - How to Account for the MGA Size (Doc ID 2808761.1)

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Attribute Clustering

• Clustering data is one of the most underused and powerful performance features

• In previous releases only possible using specific non-heap table storage (Indexed / Hash Cluster / Index organized table (IOT)) or via manual implementation, so best suited for OLTP applications

• Non-heap table implementations do have some implications that need to be carefully considered (Cluster size, secondary indexes on IOTs etc.) and limited support for later features like partitioning, offloading in Exadata etc.

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Attribute Clustering

• Attribute Clustering enables clustering of data in heap organized tables, but only during specific Direct Path operations, like INSERT APPEND, Create Table As Select, ALTER TABLE MOVE, Direct Path Load etc.

• Suites best Data Warehouse environments where Indexed / Hash Cluster and IOTs are not useful due to the limited fast data load / partition / indexing options

• Covers advanced scenarios like join clustering and clustering on multiple columns individually

• Can be combined with Zonemaps (on Exadata only unfortunately) for improving performance even further

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Attribute Clustering improves

• Index access patterns – table blocks for same index value are clustered together, improves index access performance and Buffer Cache efficiency (less table blocks need to be cached for access patterns optimized via clustering)

• Compression – table data holding the same values are clustered together, improved compression ratio, applies not only to Advanced Compression but Exadata Hybrid Columnar Compression (HCC) and InMemorycompression, too

• Exadata Storage Index usage / Zonemaps / InMemory pruning – table blocks / storage regions / InMemory Compression Units not holding the data searched for can be skipped

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Index access with scattered data

1,000 rows => visit 1,000 table blocks: 1,000 * 5ms = 5 s

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Index access with clustered data

1,000 rows => visit 10 table blocks: 10 * 5ms = 50 ms

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Nested Loop join with scattered data

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Nested Loop join with clustered data

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Attribute Clustering Linear vs. Interleaved

• Two types available

• LINEAR ORDER: Straightforward ORDER by specified column(s)

=> Only useful when using columns in specified order

• INTERLEAVED ORDER: Complex function that allows clustering being beneficial even when individual columns are specified

=> Internally implemented using undocumented functions ORA_CLUSTERING / ORA_RAWCONCAT etc.

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Attribute Clustering Linear vs. Interleaved

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Attribute Clustering

DEMO!

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06_ac_only_simple_clustering.sql06a_ac_only_simple_clustering_interleaved.sql06_ac_only_join_clustering.sql06_ac_only_join_clustering_demo.sql

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Oracle Database 21cNew Performance Features

Thank you!

Q&A

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Automatic Zonemaps / Materialized Views (Exadata only)https://docs.oracle.com/en/database/oracle/oracle-database/21/nfcon/automatic-materialized-views-264164435.html

https://docs.oracle.com/en/database/oracle/oracle-database/21/tgdba/auto_material_views.html#GUID-4E9D8731-2AE2-459A-ACFB-03C44D2A1ADD

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In Memory / Hash Join improvements

https://docs.oracle.com/en/database/oracle/oracle-database/21/inmem/optimizing-queries-with-join-groups.html#GUID-55F66F65-1568-4B53-B79E-F841B94659CA

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Persistence Memory (PMEM) support

https://docs.oracle.com/en/database/oracle/oracle-database/21/nfcon/persistent-memory-database-258797846.html

https://docs.oracle.com/en/database/oracle/oracle-database/21/admin/using-PMEM-db-support.html#GUID-A7ACCD50-30BD-49D1-AC34-14F143D4CD6D

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AskTOM Office Hours

https://asktom.oracle.com/pls/apex/f?p=100:500:::NO:RP,500::

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