.
\nAWR collects segment statistics, and this can be used to quickly understand an abnormal database growth. Here is a script I use to get, from the AWR history, the segments that have grown by more than 1% of the database size, in one hour.
\n
\nFirst I must mention that this uses only the part of AWR which is not subject to additional option. This even works in Standard Edition:<\/p>\n
NAME TYPE VALUE\n------------------------------------ ----------- ------------------------------\ncontrol_management_pack_access string NONE<\/code><\/pre>\nSo here is the query, easy to modify with different threshold:<\/p>\n
set echo on pagesize 1000\nset sqlformat ansiconsole\nselect * from (\nselect \n round(sum(SPACE_ALLOCATED_DELTA)\/1024\/1024\/1024) GBYTE_ALLOCATED\n ,trunc(max(end_interval_time),'hh24') snap_time\n ,round(sum(SPACE_ALLOCATED_DELTA)\/1024\/1024\/1024*24*(cast(max(end_interval_time) as date)-cast(min(begin_interval_time) as date))) \"GB\/hour\"\n ,owner,object_name,subobject_name,object_type\n from DBA_HIST_SEG_STAT join DBA_HIST_SEG_STAT_OBJ using (dbid,ts#,obj#,dataobj#) join dba_hist_snapshot using(dbid,snap_id)\n group by trunc(end_interval_time,'hh24'),owner,object_name,subobject_name,object_type\n) where \"GB\/hour\" > (select sum(bytes)\/1024\/1024\/1024\/1e2 \"one percent of database size\" from dba_data_files)\norder by snap_time\n;<\/code><\/pre>\nand the sample output, showing only the snapshots and segments where more than 1% of the database size has been allocated within one hour:<\/p>\n
\n GBYTE_ALLOCATED SNAP_TIME GB\/hour OWNER OBJECT_NAME SUBOBJECT_NAME OBJECT_TYPE\n --------------- --------- ------- ----- ----------- -------------- -----------\n 4 25-OCT-2017 19:00:00 4 BIGDATA SYS_LOB0000047762C00006$$ LOB\n 9 25-OCT-2017 20:00:00 9 BIGDATA SYS_LOB0000047762C00006$$ LOB\n 9 25-OCT-2017 21:00:00 9 BIGDATA SYS_LOB0000047762C00006$$ LOB\n 3 25-OCT-2017 22:00:00 3 BIGDATA SYS_LOB0000047762C00006$$ LOB\n 5 26-OCT-2017 00:00:00 5 BIGDATA SYS_LOB0000047762C00006$$ LOB\n 6 26-OCT-2017 01:00:00 6 BIGDATA SYS_LOB0000047762C00006$$ LOB\n 7 26-OCT-2017 02:00:00 7 BIGDATA SYS_LOB0000047762C00006$$ LOB\n 7 26-OCT-2017 03:00:00 7 BIGDATA SYS_LOB0000047762C00006$$ LOB\n 7 26-OCT-2017 04:00:00 7 BIGDATA SYS_LOB0000047762C00006$$ LOB\n 5 26-OCT-2017 05:00:00 5 BIGDATA SYS_LOB0000047762C00006$$ LOB\n 2 26-OCT-2017 06:00:00 2 BIGDATA SYS_LOB0000047719C00008$$ LOB\n 2 26-OCT-2017 06:00:00 2 BIGDATA SYS_LOB0000047710C00006$$ LOB\n<\/code><\/pre>\nWith this, it is easier to ask to the application owners if this growth is normal or not.<\/p>\n","protected":false},"excerpt":{"rendered":"
By Franck Pachot . AWR collects segment statistics, and this can be used to quickly understand an abnormal database growth. Here is a script I use to get, from the AWR history, the segments that have grown by more than 1% of the database size, in one hour.<\/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":[59],"tags":[422,1204,96,1171],"type_dbi":[],"class_list":["post-10608","post","type-post","status-publish","format-standard","hentry","category-oracle","tag-awr","tag-growth","tag-oracle","tag-oracle-19c"],"acf":[],"yoast_head":"\n
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