Row Chaining And Row Migration
Two of the most important concepts when it comes to Performance Tuning. As a DBA, your job is reduce Row Chaining and Row Migration as much as possible.
Row Chaining
Normally we encounter row chaining when the size of a database row is larger than the size of the database block that is used for storing it. In this situation, the row is split across more than one database block. When you need to access this row, the system access more than one database block, which results in more I/O operations.
Let’s go ahead with a scenario and assume that default block size in 8kb
Create the table DBA_GEN_BIG with the following command
Populate the table with the following command
Analyze the table to refresh the statistics with the following command
Check for chained rows with the following command
Now create a tablespace with a different block size with the following command
Move the table DBA_GEN_BIG to newly created tablespace DBAGEN
Rebuild the indexes because they are unusable after the move with the following
command
Analyze the table to refresh the statistics with the following command
Check if row chain still exists with the following command
After moving a table, such as in the preceding example, you should do an index rebuild. An index contains the row IDs of the table rows, and the row IDs identify the position of the row. The position is composed of the objects, the datafile, the block number, and the slot (row) number. When we move a table, the datafile and the block number changes, so we must rebuild the indexes.
Row chaining leads to poor performance because accessing a row in the database requires the system to read more than once DB block, even when accessing the table by the index lookup. When different block sizes are introduced in the database, remember the pros and cons of a larger block size. The larger the block size, the more likely that contention issues occur on the database block.
Chained rows affect index reads and full table scans
Keep the following points in mind
Row chaining is typically caused by insert operations
SQL statements that create or query chained rows degrade performance because of the additional I/O operations
To diagnose chained or migrated rows, use the analyze command and query the V$SYSSTAT view
To remove chained rows, set a higher PCTFREE value by using the alter table move command
Row Migration
We will migrate a row when an update to that row would cause it to not fit on the block anymore (with all of the other data that exists currently). A migration means that the entire row will move and we just leave behind the forwarding address. So, the original block just has the rowid of the new block and the entire row is moved.
A migrated row is just a special case of a chained row. A migrated row is a chained row, a chained row may or may not be a migrated row
When you analyse the table to list chained rows, it includes migrated rows as well.
Creating a CHAINED_ROWS Table
To create the table to accept data returned by an ANALYZE … LIST CHAINED ROWS statement, execute the UTLCHAIN.SQL or UTLCHN1.SQL script in $ORACLE_HOME/rdbms/admin. These scripts are provided by the database. They create a table named CHAINED_ROWS in the schema of the user submitting the script.
create table CHAINED_ROWS (
owner_name varchar2(30),
table_name varchar2(30),
cluster_name varchar2(30),
partition_name varchar2(30),
subpartition_name varchar2(30),
head_rowid rowid,
analyze_timestamp date
);After a CHAINED_ROWS table is created, you specify it in the INTO clause of the
ANALYZE statement.
Avoid Row Chaining & Migration
Increasing PCTFREE can help to avoid migrated rows. If you leave more free space available in the block, then the row has room to grow
You can also reorganize or re-create tables and indexes that have high deletion rates
The ALTER TABLE … MOVE statement enables you to relocate data of a non partitioned table or of a partition of a partitioned table into a new segment, and optionally into a different tablespace for which you have quota
Rebuild the Indexes for the Table
Conclusion
Row migration is typically caused by UPDATE operation
Row chaining is typically caused by INSERT operation.
SQL statements which are creating/querying these chained/migrated rows will degrade the performance due to more I/O work.
To diagnose chained/migrated rows use ANALYZE command , query V$SYSSTAT view
To remove chained/migrated rows use higher PCTFREE using ALTER TABLE MOVE
