Sep 07, 2013 · A common misunderstanding is that a hint of the form /*+ use_hash(table_1 table_2) */ is a directive to Oracle to do a hash join with table_1 as the build table and table_2 as the probe table. This is not the case; the hint in this form is simply a shorthand for a pair of single-table hints, viz: use_hash(table_1) use_hash(table_2).
Outer join: The combined table produced by an outer join contains all rows that existed in one table with blanks in the columns for the rows that did not exist in the second table. For instance, if table1 contains a row for Joe and a row for Sally, and table2 contains only a row for Sally, an inner join would contain only one row: the row for You can review a buffer state and call statistics data for a buffered table via SAP transaction ST10. A buffered table can have different status in different time or different status among different servers at the same time. Why is buffered table left a specific “status” and how and when it would be changed to… As per the definition of hash outer right join, the smallest of the two tables (where-in outer join is used) will be used to build the hash table, and the other table will be used as the probe table unlike hash outer join, wherein the size of the tables doesn’t play any role and the parent & child table must be used as hash & probe tables respectively. The tmp_table is a temporary table where i stored only the records and informations that will be updated in my_table. That means tmp_table.TROWID is the rowid of my_table row that should be merged. Total merged records should be: 94M on a total anount of my_table of 540M. A subtract join is the opposite of an outer join; it includes ONLY those records in one table that don't match any record in the other table. Like outer joins, there are two possible subtract joins for any two tables that you want to join; however, they are not usually referred to as "Left subtract join" or "Right subtract join." The pipe option and reduce with join_left are much faster (1.8s) (~10x faster in my case- conditional to your data of course etc..). Reduce with merge is very slow (16s) but if you replace merge with left_join then you have comparable speed as with the pipe (wee bit slower 1.9s on average but not significant). The slowest is join_all from plyr b) Table buffering increases the performance when the records of the table are read. The records of a buffered table are read directly from the local buffer of the application server on which the accessing transaction is running when the table is accessed. This eliminates time-consuming database accesses. The access improves by a factor of 10
As you know, buffer mode 5 means optimistic table buffering. Choosing table buffering rather than row buffering is usually a good choice. It lets you buffer updates to multiple records, and gives you the ability to save or revert them all in one hit. This is particularly useful if you are editing a grid.
SELECT column-names FROM table-name1 INNER JOIN table-name2 ON column-name1 = column-name2 WHERE condition Note: The INNER keyword is optional: it is the default as well as the most commmonly used JOIN operation.
Given the non buffered way, when we execute the plan, for joined row, we have to go the group node, then down to the join node and back to group node every time. but if buffered, if we execute the plan, it goes to group node first, then go to join node, without send 1 row every time, it buffered the result.
A subtract join is the opposite of an outer join; it includes ONLY those records in one table that don't match any record in the other table. Like outer joins, there are two possible subtract joins for any two tables that you want to join; however, they are not usually referred to as "Left subtract join" or "Right subtract join." The pipe option and reduce with join_left are much faster (1.8s) (~10x faster in my case- conditional to your data of course etc..). Reduce with merge is very slow (16s) but if you replace merge with left_join then you have comparable speed as with the pipe (wee bit slower 1.9s on average but not significant). The slowest is join_all from plyr