Bka 5 download

Each row from the buffer that does not have its match flag enabled is extended by NULL complements NULL values for each column in the second operand and sent for further extensions by the remaining join operations. Some cases involving the combination of one or more subqueries with one or more left joins, particularly those returning many rows, may use BNL even though it is not ideal in such instances. This is a known issue which is fixed in MySQL 8.

BKA can be applied when there is an index access to the table produced by the second join operand. Like the BNL join algorithm, the BKA join algorithm employs a join buffer to accumulate the interesting columns of the rows produced by the first operand of the join operation.

Then the BKA algorithm builds keys to access the table to be joined for all rows in the buffer and submits these keys in a batch to the database engine for index lookups. After submission of the keys, the MRR engine functions perform lookups in the index in an optimal way, fetching the rows of the joined table found by these keys, and starts feeding the BKA join algorithm with matching rows.

Each matching row is coupled with a reference to a row in the join buffer. The larger the buffer, the more sequential access is made to the right hand table of a join operation, which can significantly improve performance. Currently, the cost estimation for MRR is too pessimistic. The following setting enables BKA:. For these engines, usually the keys for all rows from the join buffer are submitted to the MRR interface at once. Engine-specific MRR functions perform index lookups for the submitted keys, get row IDs or primary keys from them, and then fetch rows for all these selected row IDs one by one by request from BKA algorithm.

Every row is returned with an association reference that enables access to the matched row in the join buffer. This improves performance because reads are in disk order rather than random order. The second scenario is used for remote storage engines such as NDB. In return, the SQL node receives a package or several packages of matching rows coupled with corresponding associations.

The BKA join algorithm takes these rows and builds new joined rows. Then a new set of keys is sent to the data nodes and the rows from the returned packages are used to build new joined rows. The process continues until the last keys from the join buffer are sent to the data nodes, and the SQL node has received and joined all rows matching these keys. This improves performance because fewer key-bearing packages sent by the SQL node to the data nodes means fewer round trips between it and the data nodes to perform the join operation.

With the first scenario, a portion of the join buffer is reserved to store row IDs primary keys selected by index lookups and passed as a parameter to the MRR functions.

There is no special buffer to store keys built for rows from the join buffer. Instead, a function that builds the key for the next row in the buffer is passed as a parameter to the MRR functions. To use a BNL or BKA hint to enable join buffering for any inner table of an outer join, join buffering must be enabled for all inner tables of the outer join. Optimizing SQL Statements.

Index Merge Optimization. Engine Condition Pushdown Optimization. Index Condition Pushdown Optimization. Nested Join Optimization.

Outer Join Optimization. Outer Join Simplification. Multi-Range Read Optimization. Function Call Optimization. Row Constructor Expression Optimization. Index Condition Pushdown Optimization. Nested Join Optimization. Outer Join Optimization. Outer Join Simplification. Multi-Range Read Optimization. Constant-Folding Optimization. Function Call Optimization. Window Function Optimization. Row Constructor Expression Optimization. Avoiding Full Table Scans.

Optimizing Subqueries with Materialization. Derived Condition Pushdown Optimization. Optimizing Performance Schema Queries. Optimizing Data Change Statements. Optimizing Database Privileges. Other Optimization Tips.

Primary Key Optimization. Foreign Key Optimization. Multiple-Column Indexes. Comparison of B-Tree and Hash Indexes. Optimizer Use of Generated Column Indexes. Optimizing Database Structure. Optimizing for Character and String Types. Optimizing for Many Tables. Limits on Number of Databases and Tables.

Optimizing for InnoDB Tables. Optimizing InnoDB Queries. Understanding the Query Execution Plan. Estimating Query Performance. Controlling the Query Optimizer.

Controlling Query Plan Evaluation. Switchable Optimizations. Midpoint Insertion Strategy. Restructuring a Key Cache. Caching of Prepared Statements and Stored Programs.

Using Symbolic Links for Databases on Unix. Or sign in with one of these services. By Cleav. By Bavarian Modding. Updated October 22, By Pogger Modifications. Updated August 28, Updated June 29, By MaxDesigns. Updated December 23, By Senfdose. Updated November 14, There are no comments to display.