Updating a materialized view in oracle

There is much seeded functionality around monitoring tables which the materialized view is dependent on using materialized view log files (explicitly designed for this purpose).For instance, I have a log file for my Oracle Apps table,[email protected] PLAN_TABLE_OUTPUT --------------------------------------------------------------------------------------------------- SQL_ID 9wwp2am6pm4dz, child number 2 ------------------------------------- select channel_id,sum(amount_sold) from sales group by channel_id Plan hash value: 2525395710 --------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | | | 18 (100)| | | 1 | VIEW | | 363 | 9438 | 18 (23)| | | 2 | UNION-ALL | | | | | | |* 3 | VIEW | VW_FOJ_0 | 100 | 2900 | 7 (15)| | |* 4 | HASH JOIN FULL OUTER | | 100 | 4300 | 7 (15)| | | 5 | VIEW | | 5 | 160 | 3 (0)| | | 6 | MAT_VIEW ACCESS FULL | MV1 | 5 | 60 | 3 (0)| | | 7 | VIEW | | 100 | 1100 | 4 (25)| | | 8 | HASH GROUP BY | | | | 4 (25)| | |* 9 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | | 10 | VIEW | | 263 | 6838 | 11 (28)| | | 11 | UNION-ALL | | | | | | |* 12 | FILTER | | | | | | | 13 | NESTED LOOPS OUTER | | 250 | 16000 | 4 (25)| | | 14 | VIEW | | 100 | 5200 | 4 (25)| | |* 15 | FILTER | | | | | | | 16 | HASH GROUP BY | | | | 4 (25)| | |* 17 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | |* 18 | INDEX UNIQUE SCAN | I_SNAP$_MV1 | 3 | 36 | 0 (0)| | | 19 | MERGE JOIN | | 13 | 871 | 7 (29)| | | 20 | MAT_VIEW ACCESS BY INDEX ROWID| MV1 | 5 | 60 | 2 (0)| | | 21 | INDEX FULL SCAN | I_SNAP$_MV1 | 5 | | 1 (0)| | |* 22 | FILTER | | | | | | |* 23 | SORT JOIN | | 100 | 5500 | 5 (40)| | | 24 | VIEW | | 100 | 5500 | 4 (25)| | | 25 | SORT GROUP BY | | | | 4 (25)| | |* 26 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | --------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("AV

When updating an existing record, is it deleted from a materialized view and then re-inserted?

To fast refresh a materialized join view, you must create a materialized view log for each of the tables referenced by the materialized view.

There are two types of materialized view logs: timestamp-based materialized view logs and commit SCN-based materialized view logs.

My problem is that I update an existing record and the trigger is being executed.

I only want this trigger to be fired for NEW records. I have a trigger like: Have you considered materialized view logs?

"."OJ_MARK" IS NULL) 4 - access(SYS_OP_MAP_NONNULL("SNA

There is much seeded functionality around monitoring tables which the materialized view is dependent on using materialized view log files (explicitly designed for this purpose).For instance, I have a log file for my Oracle Apps table,[email protected] PLAN_TABLE_OUTPUT --------------------------------------------------------------------------------------------------- SQL_ID 9wwp2am6pm4dz, child number 2 ------------------------------------- select channel_id,sum(amount_sold) from sales group by channel_id Plan hash value: 2525395710 --------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | | | 18 (100)| | | 1 | VIEW | | 363 | 9438 | 18 (23)| | | 2 | UNION-ALL | | | | | | |* 3 | VIEW | VW_FOJ_0 | 100 | 2900 | 7 (15)| | |* 4 | HASH JOIN FULL OUTER | | 100 | 4300 | 7 (15)| | | 5 | VIEW | | 5 | 160 | 3 (0)| | | 6 | MAT_VIEW ACCESS FULL | MV1 | 5 | 60 | 3 (0)| | | 7 | VIEW | | 100 | 1100 | 4 (25)| | | 8 | HASH GROUP BY | | | | 4 (25)| | |* 9 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | | 10 | VIEW | | 263 | 6838 | 11 (28)| | | 11 | UNION-ALL | | | | | | |* 12 | FILTER | | | | | | | 13 | NESTED LOOPS OUTER | | 250 | 16000 | 4 (25)| | | 14 | VIEW | | 100 | 5200 | 4 (25)| | |* 15 | FILTER | | | | | | | 16 | HASH GROUP BY | | | | 4 (25)| | |* 17 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | |* 18 | INDEX UNIQUE SCAN | I_SNAP$_MV1 | 3 | 36 | 0 (0)| | | 19 | MERGE JOIN | | 13 | 871 | 7 (29)| | | 20 | MAT_VIEW ACCESS BY INDEX ROWID| MV1 | 5 | 60 | 2 (0)| | | 21 | INDEX FULL SCAN | I_SNAP$_MV1 | 5 | | 1 (0)| | |* 22 | FILTER | | | | | | |* 23 | SORT JOIN | | 100 | 5500 | 5 (40)| | | 24 | VIEW | | 100 | 5500 | 4 (25)| | | 25 | SORT GROUP BY | | | | 4 (25)| | |* 26 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | --------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("AV

There is much seeded functionality around monitoring tables which the materialized view is dependent on using materialized view log files (explicitly designed for this purpose).For instance, I have a log file for my Oracle Apps table,[email protected] PLAN_TABLE_OUTPUT --------------------------------------------------------------------------------------------------- SQL_ID 9wwp2am6pm4dz, child number 2 ------------------------------------- select channel_id,sum(amount_sold) from sales group by channel_id Plan hash value: 2525395710 --------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | | | 18 (100)| | | 1 | VIEW | | 363 | 9438 | 18 (23)| | | 2 | UNION-ALL | | | | | | |* 3 | VIEW | VW_FOJ_0 | 100 | 2900 | 7 (15)| | |* 4 | HASH JOIN FULL OUTER | | 100 | 4300 | 7 (15)| | | 5 | VIEW | | 5 | 160 | 3 (0)| | | 6 | MAT_VIEW ACCESS FULL | MV1 | 5 | 60 | 3 (0)| | | 7 | VIEW | | 100 | 1100 | 4 (25)| | | 8 | HASH GROUP BY | | | | 4 (25)| | |* 9 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | | 10 | VIEW | | 263 | 6838 | 11 (28)| | | 11 | UNION-ALL | | | | | | |* 12 | FILTER | | | | | | | 13 | NESTED LOOPS OUTER | | 250 | 16000 | 4 (25)| | | 14 | VIEW | | 100 | 5200 | 4 (25)| | |* 15 | FILTER | | | | | | | 16 | HASH GROUP BY | | | | 4 (25)| | |* 17 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | |* 18 | INDEX UNIQUE SCAN | I_SNAP$_MV1 | 3 | 36 | 0 (0)| | | 19 | MERGE JOIN | | 13 | 871 | 7 (29)| | | 20 | MAT_VIEW ACCESS BY INDEX ROWID| MV1 | 5 | 60 | 2 (0)| | | 21 | INDEX FULL SCAN | I_SNAP$_MV1 | 5 | | 1 (0)| | |* 22 | FILTER | | | | | | |* 23 | SORT JOIN | | 100 | 5500 | 5 (40)| | | 24 | VIEW | | 100 | 5500 | 4 (25)| | | 25 | SORT GROUP BY | | | | 4 (25)| | |* 26 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | --------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("AV

When updating an existing record, is it deleted from a materialized view and then re-inserted?To fast refresh a materialized join view, you must create a materialized view log for each of the tables referenced by the materialized view.There are two types of materialized view logs: timestamp-based materialized view logs and commit SCN-based materialized view logs.My problem is that I update an existing record and the trigger is being executed.I only want this trigger to be fired for NEW records. I have a trigger like: Have you considered materialized view logs?

"."OJ_MARK" IS NULL) 4 - access(SYS_OP_MAP_NONNULL("SNA[[

There is much seeded functionality around monitoring tables which the materialized view is dependent on using materialized view log files (explicitly designed for this purpose).For instance, I have a log file for my Oracle Apps table,[email protected] PLAN_TABLE_OUTPUT --------------------------------------------------------------------------------------------------- SQL_ID 9wwp2am6pm4dz, child number 2 ------------------------------------- select channel_id,sum(amount_sold) from sales group by channel_id Plan hash value: 2525395710 --------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | | | 18 (100)| | | 1 | VIEW | | 363 | 9438 | 18 (23)| | | 2 | UNION-ALL | | | | | | |* 3 | VIEW | VW_FOJ_0 | 100 | 2900 | 7 (15)| | |* 4 | HASH JOIN FULL OUTER | | 100 | 4300 | 7 (15)| | | 5 | VIEW | | 5 | 160 | 3 (0)| | | 6 | MAT_VIEW ACCESS FULL | MV1 | 5 | 60 | 3 (0)| | | 7 | VIEW | | 100 | 1100 | 4 (25)| | | 8 | HASH GROUP BY | | | | 4 (25)| | |* 9 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | | 10 | VIEW | | 263 | 6838 | 11 (28)| | | 11 | UNION-ALL | | | | | | |* 12 | FILTER | | | | | | | 13 | NESTED LOOPS OUTER | | 250 | 16000 | 4 (25)| | | 14 | VIEW | | 100 | 5200 | 4 (25)| | |* 15 | FILTER | | | | | | | 16 | HASH GROUP BY | | | | 4 (25)| | |* 17 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | |* 18 | INDEX UNIQUE SCAN | I_SNAP$_MV1 | 3 | 36 | 0 (0)| | | 19 | MERGE JOIN | | 13 | 871 | 7 (29)| | | 20 | MAT_VIEW ACCESS BY INDEX ROWID| MV1 | 5 | 60 | 2 (0)| | | 21 | INDEX FULL SCAN | I_SNAP$_MV1 | 5 | | 1 (0)| | |* 22 | FILTER | | | | | | |* 23 | SORT JOIN | | 100 | 5500 | 5 (40)| | | 24 | VIEW | | 100 | 5500 | 4 (25)| | | 25 | SORT GROUP BY | | | | 4 (25)| | |* 26 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | --------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("AV$0"."OJ_MARK" IS NULL) 4 - access(SYS_OP_MAP_NONNULL("SNA$0"."CHANNEL_ID")=SYS_OP_MAP_NONNULL("AV$0"."GB0")) 9 - filter("MAS$"."SNAPTIME$$"TO_DATE(' 2017-01-05 ', 'syyyy-mm-dd hh24:mi:ss')) 12 - filter(CASE WHEN ROWID IS NOT NULL THEN 1 ELSE NULL END IS NULL) 15 - filter(SUM(DECODE(DECODE("MAS$"."OLD_NEW$$",'N','I','D'),'I',1,(-1))) Isn’t it nice that also the good old stuff gets enhanced instead of only the fancy new things like the In-Memory Option? Having a fact table that is partitioned offers two additional benefits for materialized views.

||

There is much seeded functionality around monitoring tables which the materialized view is dependent on using materialized view log files (explicitly designed for this purpose).

For instance, I have a log file for my Oracle Apps table,inv.mtl_system_items_b.

]]"."CHANNEL_ID")=SYS_OP_MAP_NONNULL("AV[[

There is much seeded functionality around monitoring tables which the materialized view is dependent on using materialized view log files (explicitly designed for this purpose).For instance, I have a log file for my Oracle Apps table,[email protected] PLAN_TABLE_OUTPUT --------------------------------------------------------------------------------------------------- SQL_ID 9wwp2am6pm4dz, child number 2 ------------------------------------- select channel_id,sum(amount_sold) from sales group by channel_id Plan hash value: 2525395710 --------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | | | 18 (100)| | | 1 | VIEW | | 363 | 9438 | 18 (23)| | | 2 | UNION-ALL | | | | | | |* 3 | VIEW | VW_FOJ_0 | 100 | 2900 | 7 (15)| | |* 4 | HASH JOIN FULL OUTER | | 100 | 4300 | 7 (15)| | | 5 | VIEW | | 5 | 160 | 3 (0)| | | 6 | MAT_VIEW ACCESS FULL | MV1 | 5 | 60 | 3 (0)| | | 7 | VIEW | | 100 | 1100 | 4 (25)| | | 8 | HASH GROUP BY | | | | 4 (25)| | |* 9 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | | 10 | VIEW | | 263 | 6838 | 11 (28)| | | 11 | UNION-ALL | | | | | | |* 12 | FILTER | | | | | | | 13 | NESTED LOOPS OUTER | | 250 | 16000 | 4 (25)| | | 14 | VIEW | | 100 | 5200 | 4 (25)| | |* 15 | FILTER | | | | | | | 16 | HASH GROUP BY | | | | 4 (25)| | |* 17 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | |* 18 | INDEX UNIQUE SCAN | I_SNAP$_MV1 | 3 | 36 | 0 (0)| | | 19 | MERGE JOIN | | 13 | 871 | 7 (29)| | | 20 | MAT_VIEW ACCESS BY INDEX ROWID| MV1 | 5 | 60 | 2 (0)| | | 21 | INDEX FULL SCAN | I_SNAP$_MV1 | 5 | | 1 (0)| | |* 22 | FILTER | | | | | | |* 23 | SORT JOIN | | 100 | 5500 | 5 (40)| | | 24 | VIEW | | 100 | 5500 | 4 (25)| | | 25 | SORT GROUP BY | | | | 4 (25)| | |* 26 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | --------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("AV$0"."OJ_MARK" IS NULL) 4 - access(SYS_OP_MAP_NONNULL("SNA$0"."CHANNEL_ID")=SYS_OP_MAP_NONNULL("AV$0"."GB0")) 9 - filter("MAS$"."SNAPTIME$$"TO_DATE(' 2017-01-05 ', 'syyyy-mm-dd hh24:mi:ss')) 12 - filter(CASE WHEN ROWID IS NOT NULL THEN 1 ELSE NULL END IS NULL) 15 - filter(SUM(DECODE(DECODE("MAS$"."OLD_NEW$$",'N','I','D'),'I',1,(-1))) Isn’t it nice that also the good old stuff gets enhanced instead of only the fancy new things like the In-Memory Option? Having a fact table that is partitioned offers two additional benefits for materialized views.

||

There is much seeded functionality around monitoring tables which the materialized view is dependent on using materialized view log files (explicitly designed for this purpose).

For instance, I have a log file for my Oracle Apps table,inv.mtl_system_items_b.

]]"."GB0")) 9 - filter("MAS$"."SNAPTIME$$"TO_DATE(' 2017-01-05 ', 'syyyy-mm-dd hh24:mi:ss')) 12 - filter(CASE WHEN ROWID IS NOT NULL THEN 1 ELSE NULL END IS NULL) 15 - filter(SUM(DECODE(DECODE("MAS$"."OLD_NEW$$",'N','I','D'),'I',1,(-1))) Isn’t it nice that also the good old stuff gets enhanced instead of only the fancy new things like the In-Memory Option? Having a fact table that is partitioned offers two additional benefits for materialized views.

"."OJ_MARK" IS NULL) 4 - access(SYS_OP_MAP_NONNULL("SNA[[

There is much seeded functionality around monitoring tables which the materialized view is dependent on using materialized view log files (explicitly designed for this purpose).For instance, I have a log file for my Oracle Apps table,[email protected] PLAN_TABLE_OUTPUT --------------------------------------------------------------------------------------------------- SQL_ID 9wwp2am6pm4dz, child number 2 ------------------------------------- select channel_id,sum(amount_sold) from sales group by channel_id Plan hash value: 2525395710 --------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | | | 18 (100)| | | 1 | VIEW | | 363 | 9438 | 18 (23)| | | 2 | UNION-ALL | | | | | | |* 3 | VIEW | VW_FOJ_0 | 100 | 2900 | 7 (15)| | |* 4 | HASH JOIN FULL OUTER | | 100 | 4300 | 7 (15)| | | 5 | VIEW | | 5 | 160 | 3 (0)| | | 6 | MAT_VIEW ACCESS FULL | MV1 | 5 | 60 | 3 (0)| | | 7 | VIEW | | 100 | 1100 | 4 (25)| | | 8 | HASH GROUP BY | | | | 4 (25)| | |* 9 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | | 10 | VIEW | | 263 | 6838 | 11 (28)| | | 11 | UNION-ALL | | | | | | |* 12 | FILTER | | | | | | | 13 | NESTED LOOPS OUTER | | 250 | 16000 | 4 (25)| | | 14 | VIEW | | 100 | 5200 | 4 (25)| | |* 15 | FILTER | | | | | | | 16 | HASH GROUP BY | | | | 4 (25)| | |* 17 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | |* 18 | INDEX UNIQUE SCAN | I_SNAP$_MV1 | 3 | 36 | 0 (0)| | | 19 | MERGE JOIN | | 13 | 871 | 7 (29)| | | 20 | MAT_VIEW ACCESS BY INDEX ROWID| MV1 | 5 | 60 | 2 (0)| | | 21 | INDEX FULL SCAN | I_SNAP$_MV1 | 5 | | 1 (0)| | |* 22 | FILTER | | | | | | |* 23 | SORT JOIN | | 100 | 5500 | 5 (40)| | | 24 | VIEW | | 100 | 5500 | 4 (25)| | | 25 | SORT GROUP BY | | | | 4 (25)| | |* 26 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | --------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("AV$0"."OJ_MARK" IS NULL) 4 - access(SYS_OP_MAP_NONNULL("SNA$0"."CHANNEL_ID")=SYS_OP_MAP_NONNULL("AV$0"."GB0")) 9 - filter("MAS$"."SNAPTIME$$"TO_DATE(' 2017-01-05 ', 'syyyy-mm-dd hh24:mi:ss')) 12 - filter(CASE WHEN ROWID IS NOT NULL THEN 1 ELSE NULL END IS NULL) 15 - filter(SUM(DECODE(DECODE("MAS$"."OLD_NEW$$",'N','I','D'),'I',1,(-1))) Isn’t it nice that also the good old stuff gets enhanced instead of only the fancy new things like the In-Memory Option? Having a fact table that is partitioned offers two additional benefits for materialized views.

||

There is much seeded functionality around monitoring tables which the materialized view is dependent on using materialized view log files (explicitly designed for this purpose).

For instance, I have a log file for my Oracle Apps table,inv.mtl_system_items_b.

]]"."CHANNEL_ID")=SYS_OP_MAP_NONNULL("AV[[

There is much seeded functionality around monitoring tables which the materialized view is dependent on using materialized view log files (explicitly designed for this purpose).For instance, I have a log file for my Oracle Apps table,[email protected] PLAN_TABLE_OUTPUT --------------------------------------------------------------------------------------------------- SQL_ID 9wwp2am6pm4dz, child number 2 ------------------------------------- select channel_id,sum(amount_sold) from sales group by channel_id Plan hash value: 2525395710 --------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | | | 18 (100)| | | 1 | VIEW | | 363 | 9438 | 18 (23)| | | 2 | UNION-ALL | | | | | | |* 3 | VIEW | VW_FOJ_0 | 100 | 2900 | 7 (15)| | |* 4 | HASH JOIN FULL OUTER | | 100 | 4300 | 7 (15)| | | 5 | VIEW | | 5 | 160 | 3 (0)| | | 6 | MAT_VIEW ACCESS FULL | MV1 | 5 | 60 | 3 (0)| | | 7 | VIEW | | 100 | 1100 | 4 (25)| | | 8 | HASH GROUP BY | | | | 4 (25)| | |* 9 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | | 10 | VIEW | | 263 | 6838 | 11 (28)| | | 11 | UNION-ALL | | | | | | |* 12 | FILTER | | | | | | | 13 | NESTED LOOPS OUTER | | 250 | 16000 | 4 (25)| | | 14 | VIEW | | 100 | 5200 | 4 (25)| | |* 15 | FILTER | | | | | | | 16 | HASH GROUP BY | | | | 4 (25)| | |* 17 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | |* 18 | INDEX UNIQUE SCAN | I_SNAP$_MV1 | 3 | 36 | 0 (0)| | | 19 | MERGE JOIN | | 13 | 871 | 7 (29)| | | 20 | MAT_VIEW ACCESS BY INDEX ROWID| MV1 | 5 | 60 | 2 (0)| | | 21 | INDEX FULL SCAN | I_SNAP$_MV1 | 5 | | 1 (0)| | |* 22 | FILTER | | | | | | |* 23 | SORT JOIN | | 100 | 5500 | 5 (40)| | | 24 | VIEW | | 100 | 5500 | 4 (25)| | | 25 | SORT GROUP BY | | | | 4 (25)| | |* 26 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | --------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("AV$0"."OJ_MARK" IS NULL) 4 - access(SYS_OP_MAP_NONNULL("SNA$0"."CHANNEL_ID")=SYS_OP_MAP_NONNULL("AV$0"."GB0")) 9 - filter("MAS$"."SNAPTIME$$"TO_DATE(' 2017-01-05 ', 'syyyy-mm-dd hh24:mi:ss')) 12 - filter(CASE WHEN ROWID IS NOT NULL THEN 1 ELSE NULL END IS NULL) 15 - filter(SUM(DECODE(DECODE("MAS$"."OLD_NEW$$",'N','I','D'),'I',1,(-1))) Isn’t it nice that also the good old stuff gets enhanced instead of only the fancy new things like the In-Memory Option? Having a fact table that is partitioned offers two additional benefits for materialized views.

||

There is much seeded functionality around monitoring tables which the materialized view is dependent on using materialized view log files (explicitly designed for this purpose).

For instance, I have a log file for my Oracle Apps table,inv.mtl_system_items_b.

]]"."GB0")) 9 - filter("MAS$"."SNAPTIME$$"TO_DATE(' 2017-01-05 ', 'syyyy-mm-dd hh24:mi:ss')) 12 - filter(CASE WHEN ROWID IS NOT NULL THEN 1 ELSE NULL END IS NULL) 15 - filter(SUM(DECODE(DECODE("MAS$"."OLD_NEW$$",'N','I','D'),'I',1,(-1))) Isn’t it nice that also the good old stuff gets enhanced instead of only the fancy new things like the In-Memory Option? Having a fact table that is partitioned offers two additional benefits for materialized views.

"."CHANNEL_ID")=SYS_OP_MAP_NONNULL("AV[[

There is much seeded functionality around monitoring tables which the materialized view is dependent on using materialized view log files (explicitly designed for this purpose).For instance, I have a log file for my Oracle Apps table,[email protected] PLAN_TABLE_OUTPUT --------------------------------------------------------------------------------------------------- SQL_ID 9wwp2am6pm4dz, child number 2 ------------------------------------- select channel_id,sum(amount_sold) from sales group by channel_id Plan hash value: 2525395710 --------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | | | 18 (100)| | | 1 | VIEW | | 363 | 9438 | 18 (23)| | | 2 | UNION-ALL | | | | | | |* 3 | VIEW | VW_FOJ_0 | 100 | 2900 | 7 (15)| | |* 4 | HASH JOIN FULL OUTER | | 100 | 4300 | 7 (15)| | | 5 | VIEW | | 5 | 160 | 3 (0)| | | 6 | MAT_VIEW ACCESS FULL | MV1 | 5 | 60 | 3 (0)| | | 7 | VIEW | | 100 | 1100 | 4 (25)| | | 8 | HASH GROUP BY | | | | 4 (25)| | |* 9 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | | 10 | VIEW | | 263 | 6838 | 11 (28)| | | 11 | UNION-ALL | | | | | | |* 12 | FILTER | | | | | | | 13 | NESTED LOOPS OUTER | | 250 | 16000 | 4 (25)| | | 14 | VIEW | | 100 | 5200 | 4 (25)| | |* 15 | FILTER | | | | | | | 16 | HASH GROUP BY | | | | 4 (25)| | |* 17 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | |* 18 | INDEX UNIQUE SCAN | I_SNAP$_MV1 | 3 | 36 | 0 (0)| | | 19 | MERGE JOIN | | 13 | 871 | 7 (29)| | | 20 | MAT_VIEW ACCESS BY INDEX ROWID| MV1 | 5 | 60 | 2 (0)| | | 21 | INDEX FULL SCAN | I_SNAP$_MV1 | 5 | | 1 (0)| | |* 22 | FILTER | | | | | | |* 23 | SORT JOIN | | 100 | 5500 | 5 (40)| | | 24 | VIEW | | 100 | 5500 | 4 (25)| | | 25 | SORT GROUP BY | | | | 4 (25)| | |* 26 | TABLE ACCESS FULL | MLOG$_SALES | 2 | 74 | 3 (0)| | --------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("AV$0"."OJ_MARK" IS NULL) 4 - access(SYS_OP_MAP_NONNULL("SNA$0"."CHANNEL_ID")=SYS_OP_MAP_NONNULL("AV$0"."GB0")) 9 - filter("MAS$"."SNAPTIME$$"TO_DATE(' 2017-01-05 ', 'syyyy-mm-dd hh24:mi:ss')) 12 - filter(CASE WHEN ROWID IS NOT NULL THEN 1 ELSE NULL END IS NULL) 15 - filter(SUM(DECODE(DECODE("MAS$"."OLD_NEW$$",'N','I','D'),'I',1,(-1))) Isn’t it nice that also the good old stuff gets enhanced instead of only the fancy new things like the In-Memory Option? Having a fact table that is partitioned offers two additional benefits for materialized views.

||

There is much seeded functionality around monitoring tables which the materialized view is dependent on using materialized view log files (explicitly designed for this purpose).

For instance, I have a log file for my Oracle Apps table,inv.mtl_system_items_b.

]]"."GB0")) 9 - filter("MAS$"."SNAPTIME$$"TO_DATE(' 2017-01-05 ', 'syyyy-mm-dd hh24:mi:ss')) 12 - filter(CASE WHEN ROWID IS NOT NULL THEN 1 ELSE NULL END IS NULL) 15 - filter(SUM(DECODE(DECODE("MAS$"."OLD_NEW$$",'N','I','D'),'I',1,(-1))) Isn’t it nice that also the good old stuff gets enhanced instead of only the fancy new things like the In-Memory Option? Having a fact table that is partitioned offers two additional benefits for materialized views.

[[

When updating an existing record, is it deleted from a materialized view and then re-inserted?

To fast refresh a materialized join view, you must create a materialized view log for each of the tables referenced by the materialized view.

There are two types of materialized view logs: timestamp-based materialized view logs and commit SCN-based materialized view logs.

My problem is that I update an existing record and the trigger is being executed.

I only want this trigger to be fired for NEW records. I have a trigger like: Have you considered materialized view logs?

||

When updating an existing record, is it deleted from a materialized view and then re-inserted?To fast refresh a materialized join view, you must create a materialized view log for each of the tables referenced by the materialized view.There are two types of materialized view logs: timestamp-based materialized view logs and commit SCN-based materialized view logs.My problem is that I update an existing record and the trigger is being executed.I only want this trigger to be fired for NEW records. I have a trigger like: Have you considered materialized view logs?

]]

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