{"id":10748,"date":"2018-01-10T21:15:27","date_gmt":"2018-01-10T20:15:27","guid":{"rendered":"https:\/\/www.dbi-services.com\/blog\/automatic-data-optimization-part-i-compression-tiering\/"},"modified":"2023-06-09T16:52:20","modified_gmt":"2023-06-09T14:52:20","slug":"automatic-data-optimization-part-i-compression-tiering","status":"publish","type":"post","link":"https:\/\/www.dbi-services.com\/blog\/automatic-data-optimization-part-i-compression-tiering\/","title":{"rendered":"Automatic Data Optimization Part I : Compression Tiering"},"content":{"rendered":"

By Mouhamadou Diaw<\/strong><\/p>\n

Nowadays data are increasing more and more. And some challenges we can face can be how to reduce storage costs and how to improve performance. With Oracle 12c, the feature Automatic Data Optimization (ADO) can help us.
\nIn this first blog we will see how we can use ADO to compress data under predefined conditions.
\nADO is part of Information Lifecycle Management (ILM). Note that ADO requires Advanced Compression Option.
\nIn this article we are using oracle a 12.1.0.2 non-CDB database.
\nFirst let\u2019s create the user we will use for the demonstration
\n
\nSQL> create user app identified by app default tablespace users temporary tablespace temp;
\nUser created.
\n.
\nSQL> grant create session,create table,alter tablespace,select any dictionary,unlimited tablespace to app;
\nGrant succeeded.
\n<\/code>
\nNow with this user let\u2019s create a table and let\u2019s insert some data
\nSQL> show user
\nUSER is \"APP\"
\nSQL> create table article(idart number,designation varchar2(20));
\nTable created.
\n.
\nSQL> select count(*) from article;
\nCOUNT(*)
\n----------
\n1048576
\n<\/code>
\nWhat we will demonstrate is how data in table ARTICLE can be automatically compressed if they are not modified within the last 30 days for example. It\u2019s just an example and there are many other conditions.
\nFirst let\u2019s verify that the compression attribute of the table article is disabled
\nSQL> show user
\nUSER is \"APP\"
\nSQL> SELECT compression, compress_for FROM user_tables WHERE table_name = 'ARTICLE';
\nCOMPRESS COMPRESS_FOR
\n-------- ------------------------------
\nDISABLED
\n<\/code>
\nWe can also confirm that there is no compression in the table using this oracle script.
\n[oracle@serverora1 ]$ cat comp_art.sql
\nSELECT CASE compression_type
\nWHEN 1 THEN 'No Compression'
\nWHEN 2 THEN 'Advanced compression level'
\nWHEN 4 THEN 'Hybrid Columnar Compression for Query High'
\nWHEN 8 THEN 'Hybrid Columnar Compression for Query Low'
\nWHEN 16 THEN 'Hybrid Columnar Compression for Archive High'
\nWHEN 32 THEN 'Hybrid Columnar Compression for Archive Low'
\nWHEN 64 THEN 'Compressed row'
\nWHEN 128 THEN 'High compression level for LOB operations'
\nWHEN 256 THEN 'Medium compression level for LOB operations'
\nWHEN 512 THEN 'Low compression level for LOB operations'
\nWHEN 1000 THEN 'Minimum required number of LOBs in the object for which LOB compression ratio is to be estimated'
\nWHEN 4096 THEN 'Basic compression level'
\nWHEN 5000 THEN 'Maximum number of LOBs used to compute the LOB compression ratio'
\nWHEN 1000000 THEN 'Minimum required number of rows in the object for which HCC ratio is to be estimated'
\nWHEN -1 THEN 'To indicate the use of all the rows in the object to estimate HCC ratio'
\nWHEN 1 THEN 'Identifies the object whose compression ratio is estimated as of type table'
\nELSE 'Unknown Compression Type'
\nEND AS compression_type, n as num_rows
\nFROM (SELECT compression_type, Count(*) n
\nFROM (SELECT dbms_compression.Get_compression_type(USER, 'ARTICLE', ROWID) AS COMPRESSION_TYPE
\nFROM app.article)
\nGROUP BY compression_type
\n);
\n[oracle@serverora1 ]$
\n<\/code>
\nBelow we can see that there is no compressed data
\nSQL> col COMPRESSION_TYPE for a20
\nSQL> @comp_art
\nCOMPRESSION_TYPE NUM_ROWS
\n-------------------- ----------
\nNo Compression 1048576
\n<\/code>
\nTo use ADO for compression, the Heat Map must be enabled. Indeed once enabled, Heat Map will collect statistics required for ADO actions. All accesses are tracked by the in-memory activity tracking module. So let\u2019s enable the Heat Map at instance level
\n
\nSQL> show parameter heat
\nNAME TYPE VALUE
\n------------------------------------ ----------- ------------------------------
\nheat_map string OFF
\n.
\nSQL> alter system set heat_map=ON scope=both;
\nSystem altered.
\n.
\nSQL> show parameter heat
\nNAME TYPE VALUE
\n------------------------------------ ----------- ------------------------------
\nheat_map string ON
\n<\/code>
\nBy default the policy time is specified in days. If we query the DBA_ILMPARAMETERS, the value for POLICY TIME determines if ADO policies are specified in seconds or days. Values are 1 for seconds or 0 for days (default).
\n
\nSQL> col name for a20
\nSQL> select * from DBA_ILMPARAMETERS;
\nNAME VALUE
\n-------------------- ----------
\nENABLED 1
\nRETENTION TIME 30
\nJOB LIMIT 2
\nEXECUTION MODE 2
\nEXECUTION INTERVAL 15
\nTBS PERCENT USED 85
\nTBS PERCENT FREE 25
\nPOLICY TIME 0
\n8 rows selected.
\n<\/code>
\nBut in our demonstration we will not wait 30 days, so we will set the policy time in seconds instead of days and then if we specify 30 days this will mean 30 seconds.
\n
\nSQL> EXEC dbms_ilm_admin.customize_ilm(dbms_ilm_admin.POLICY_TIME,dbms_ilm_admin.ILM_POLICY_IN_SECONDS);
\nPL\/SQL procedure successfully completed.
\n.
\nSQL> select * from DBA_ILMPARAMETERS;
\nNAME VALUE
\n-------------------- ----------
\nENABLED 1
\nRETENTION TIME 30
\nJOB LIMIT 2
\nEXECUTION MODE 2
\nEXECUTION INTERVAL 15
\nTBS PERCENT USED 85
\nTBS PERCENT FREE 25
\nPOLICY TIME 1
\n8 rows selected.
\nSQL>
\n<\/code>
\nBefore adding the ADO policy, we can verify that heat map statistics are already collected.
\n
\nSELECT OBJECT_NAME, to_char(TRACK_TIME,'DD-MON-YYYY HH24:MI:SS'), SEGMENT_WRITE \"Seg_write\",
\nSEGMENT_READ \"Seg_read\", FULL_SCAN, LOOKUP_SCAN
\nFROM v$heat_map_segment WHERE object_name='ARTICLE';
\n.
\nOBJECT_NAME TO_CHAR(TRACK_TIME,'DD-MON-YY Seg Seg FUL LOO
\n------------------------------ ----------------------------- --- --- --- ---
\nARTICLE 08-JAN-2018 17:02:21 NO NO YES NO
\nSQL>
\n<\/code>
\nNow let\u2019s add a segment level<\/strong> row compression policy on ARTICLE table that will compress the segment when no modification on the segment will have occurred in the last 30 days (considered as 30 seconds due to the policy time).
\n
\nSQL> show user
\nUSER is \"APP\"
\nSQL> ALTER TABLE app.article ILM ADD POLICY ROW STORE COMPRESS ADVANCED SEGMENT<\/strong> AFTER 30 DAYS OF NO MODIFICATION;
\nTable altered.
\nSQL>
\n<\/code>
\nWe can use the user_ilmdatamovementpolicies and user_ilmobjects with user app to verify the policy.
\n
\nSQL> show user
\nUSER is \"APP\"
\nSQL> SELECT policy_name, action_type, scope, compression_level, condition_type, condition_days FROM user_ilmdatamovementpolicies ORDER BY policy_name;
\nPOLICY_NAME ACTION_TYPE SCOPE COMPRESSION_LEVEL CONDITION_TYPE CONDITION_DAYS
\n--------------- ----------- ------- ----------------- ---------------------- --------------
\nP45 COMPRESSION SEGMENT ADVANCED LAST MODIFICATION TIME 30
\n.
\nSQL> SELECT policy_name, object_name, enabled FROM user_ilmobjects;
\nPOLICY_NAME OBJECT_NAME ENA
\n--------------- -------------------- ---
\nP45 ARTICLE YES
\n<\/code>
\nFlush the heat map statistics from memory to disk and let\u2019s wait 30 days ( in fact 30 seconds because don\u2019t forget the policy_time was changed to seconds instead of days). Can be also sometimes useful to gather the statistics of the table
\n
\nSQL> EXEC dbms_ilm.flush_all_segments;
\nPL\/SQL procedure successfully completed.
\nSQL>
\n<\/code>
\nBy default ADO policies are automatically triggered during maintenance window. But in this demonstration we are going to manually execute the policy without waiting the maintenance window.
\n
\nSQL> show user
\nUSER is \"APP\"
\nSQL> DECLARE
\nv_executionid number;
\nBEGIN
\ndbms_ilm.execute_ILM (ILM_SCOPE => dbms_ilm.SCOPE_SCHEMA,
\nexecution_mode => dbms_ilm.ilm_execution_offline,
\ntask_id => v_executionid);
\nEND;
\n\/
\nPL\/SQL procedure successfully completed.
\nSQL>
\n<\/code>
\nSome info about the job can be obtained in the following views
\n
\nSQL> SELECT task_id, start_time as start_time FROM user_ilmtasks order by 1;
\nTASK_ID
\n----------
\nSTART_TIME
\n---------------------------------------------------------------------------
\n26
\n08-JAN-18 05.28.45.788076 PM
\nSQL>
\n.
\nSQL> SELECT task_id, job_name, job_state, completion_time completion
\nFROM user_ilmresults ORDER BY 1 ;
\nTASK_ID
\n----------
\nJOB_NAME
\n--------------------------------------------------------------------------------
\nJOB_STATE
\n-----------------------------------
\nCOMPLETION
\n---------------------------------------------------------------------------
\n26
\nILMJOB98
\nCOMPLETED SUCCESSFULLY
\n08-JAN-18 05.28.49.368009 PM
\n<\/code>
\nWe can see that job run successfully. And we can verify that compression in table ARTICLE is now enabled
\n
\nSQL> SELECT compression, compress_for FROM user_tables WHERE table_name = 'ARTICLE';
\nCOMPRESS COMPRESS_FOR
\n-------- ------------------------------
\nENABLED ADVANCED
\nSQL>
\n<\/code>
\nAnd we also can see that all rows are compressed.
\n
\nSQL> col COMPRESSION_TYPE for a20
\nSQL> @comp_art.sql
\nCOMPRESSION_TYPE NUM_ROWS
\n-------------------- ----------
\nAdvanced compression 1048576
\nlevel
\n<\/code>
\nConclusion <\/strong>: In this first part we have seen that how ADO can help us for compression. In a second post we will talk about data movement with ADO.<\/p>\n","protected":false},"excerpt":{"rendered":"

By Mouhamadou Diaw Nowadays data are increasing more and more. And some challenges we can face can be how to reduce storage costs and how to improve performance. With Oracle 12c, the feature Automatic Data Optimization (ADO) can help us. In this first blog we will see how we can use ADO to compress data […]<\/p>\n","protected":false},"author":27,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[229],"tags":[1251,1252,209,1253],"type_dbi":[],"class_list":["post-10748","post","type-post","status-publish","format-standard","hentry","category-database-administration-monitoring","tag-ado","tag-automatic-data-optimization","tag-oracle-12c","tag-oracle-ilm"],"acf":[],"yoast_head":"\nAutomatic Data Optimization Part I : Compression Tiering - dbi Blog<\/title>\n<meta name=\"description\" content=\"oracle ILM, Automatic Data Optimization, ADO, oracle 12c, compression\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.dbi-services.com\/blog\/automatic-data-optimization-part-i-compression-tiering\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Automatic Data Optimization Part I : Compression Tiering\" \/>\n<meta property=\"og:description\" content=\"oracle ILM, Automatic Data Optimization, ADO, oracle 12c, compression\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.dbi-services.com\/blog\/automatic-data-optimization-part-i-compression-tiering\/\" \/>\n<meta property=\"og:site_name\" content=\"dbi Blog\" \/>\n<meta property=\"article:published_time\" content=\"2018-01-10T20:15:27+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-06-09T14:52:20+00:00\" \/>\n<meta name=\"author\" content=\"Oracle Team\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Oracle Team\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.dbi-services.com\/blog\/automatic-data-optimization-part-i-compression-tiering\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.dbi-services.com\/blog\/automatic-data-optimization-part-i-compression-tiering\/\"},\"author\":{\"name\":\"Oracle Team\",\"@id\":\"https:\/\/www.dbi-services.com\/blog\/#\/schema\/person\/66ab87129f2d357f09971bc7936a77ee\"},\"headline\":\"Automatic Data Optimization Part I : Compression Tiering\",\"datePublished\":\"2018-01-10T20:15:27+00:00\",\"dateModified\":\"2023-06-09T14:52:20+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.dbi-services.com\/blog\/automatic-data-optimization-part-i-compression-tiering\/\"},\"wordCount\":514,\"commentCount\":0,\"keywords\":[\"ADO\",\"Automatic Data Optimization\",\"Oracle 12c\",\"oracle ILM\"],\"articleSection\":[\"Database Administration & Monitoring\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.dbi-services.com\/blog\/automatic-data-optimization-part-i-compression-tiering\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.dbi-services.com\/blog\/automatic-data-optimization-part-i-compression-tiering\/\",\"url\":\"https:\/\/www.dbi-services.com\/blog\/automatic-data-optimization-part-i-compression-tiering\/\",\"name\":\"Automatic Data Optimization Part I : Compression Tiering - 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