enq: TX - index contention Wait Event , Cause, Related SQL queries, Possible Resolution



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The "enq: TX - index contention" wait event in Oracle occurs when multiple database sessions are contending for locks on the same index block. This contention can lead to performance issues as sessions have to wait for the locks to be released before they can proceed with their operations.


 In Oracle, locks are used to control access to data structures, including index blocks, to maintain data consistency and integrity. 

The "enq: TX - index contention" wait event specifically indicates contention for locks on an index block. 

This wait event typically occurs when multiple sessions are trying to modify or update the same index block concurrently, causing contention and blocking.
The reason for this is the index block splits while inserting a new row into the index. The transactions will have to wait for TX lock in mode 4, until the session that is doing the block splits completes the operations. 
 A session will initiate a index block split, when it can’t find space in an index block where it needs to insert a new row. Before starting the split, it would clean out all the keys in the block to check whether there is enough sufficient space in the deleted block. 

 Splitter has to do the following activities: 

 o Allocate a new block. 
 o Copy a percentage of rows to the new buffer. 
 o Add the new buffer to the index structure and commit the operation. 

Identifying Sessions with "enq: TX - index contention" Wait Event:
WHERE EVENT = 'enq: TX - index contention';

Identifying Indexes and Locking Sessions:

FROM DBA_BLOCKERS; -- Sessions holding locks on indexes

FROM DBA_WAITERS; -- Sessions waiting for locks on indexes


 Optimize SQL Statements: Review and optimize SQL statements that are causing the contention. Ensure that queries are efficient and minimize the need for index-level locks. 

 Index Design: Consider reevaluating the design of the index. Properly designed indexes can reduce the likelihood of index contention. Ensure that indexes are used efficiently in queries. 

Reverse Key Indexes :Rebuild the as reverse key indexes or hash partition the indexes which are listed in the 'Segments by Row Lock Waits' of the AWR reports. These indexes are excellent for insert performance. But the downside of it is that, it may affect the performance of index range scans

Hash partitioned global indexes :When an index is monotonically growing because of a sequence or date key, global hash-partitioned indexes improve performance by spreading out the contention. Thus, hash-partitioned global indexes can improve the performance of indexes in which a small number of leaf blocks in the index have high contention in multi-user OLTP environments

Rebuild indexes: If many rows are deleted or it is an skewed indexes rebuilding will help for a while

 Transaction Isolation Levels: Adjust the transaction isolation level (e.g., using READ COMMITTED) to control the level of locking and contention. 

 Lock Timeout: Implement lock timeouts to prevent long waits for locks on indexes. Sessions can be configured to wait only for a certain period before giving up and retrying. 

Batch Processing: If possible, batch similar operations together to reduce the likelihood of contention. For example, update multiple rows that share the same index block in a single transaction. 

Concurrency Control: Implement application-level concurrency control mechanisms to coordinate access to shared indexes. This could involve using semaphores or other synchronization techniques. 

Index Block Splitting: Oracle automatically splits index blocks when they become too full. However, this process can cause contention. Monitor and adjust the PCTFREE and PCTUSED index parameters to control block splits. 

Monitor Locking Activity: Continuously monitor the database for locking and contention issues using Oracle's performance monitoring tools. Database Design: Review your database design to minimize contention. This could involve denormalization or partitioning of data. 

Partitioned Indexes: Consider using partitioned indexes to distribute the index data across multiple partitions, reducing contention on a single index block. 


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