Index Strategy Review for 5TB Databases

By Tom Nonmacher

As databases grow into the multi-terabyte range, the management of indexes becomes increasingly important. A well-planned index strategy can dramatically improve query performance, while a poorly thought out index strategy can lead to wasted disk space and even slow down query execution. Today, we will be discussing index strategies for 5TB databases using a variety of technologies, including SQL Server 2012, SQL Server 2014, MySQL 5.6, DB2 10.5, and Azure SQL.

Let's begin with SQL Server 2012 and 2014. A vital technique for managing indexes in large databases is the use of partitioning. Partitioning allows you to divide your table into smaller, more manageable pieces. It can also help to improve query performance, as the database engine can process data from each partition in parallel. Here's an example of how to partition a table in SQL Server: 


-- Create the partition function
CREATE PARTITION FUNCTION pf_PartitionSample (int)
AS RANGE LEFT FOR VALUES (1000, 2000, 3000, 4000, 5000);
-- Create the partition scheme
CREATE PARTITION SCHEME ps_PartitionSample
AS PARTITION pf_PartitionSample
TO (FG1, FG2, FG3, FG4, FG5, FG6);
-- Create the partitioned table
CREATE TABLE tbl_PartitionSample
(
ID int NOT NULL,
Value varchar(10) NOT NULL
)
ON ps_PartitionSample (ID);

In MySQL 5.6, we can use the EXPLAIN command to analyze our queries and understand how our indexes are being used. This can be invaluable in identifying inefficient queries and indexes. For example: 


EXPLAIN SELECT * FROM orders WHERE customer_id = 123;

This will return a table of information, including the type of join used, the table referenced, possible keys that can be used, the key that was used, the key length, the number of rows scanned, and additional information about how the query was executed.

For IBM's DB2 10.5, the RUNSTATS utility is a valuable tool for managing indexes in large databases. RUNSTATS collects statistics about the physical characteristics of tables and indexes, which the database engine can then use to optimize query performance. It can be run as follows: 


RUNSTATS ON TABLE schema.table
WITH DISTRIBUTION AND DETAILED INDEXES ALL

Finally, for Azure SQL, it is important to regularly rebuild and reorganize your indexes to maintain their efficiency. This can be accomplished using the ALTER INDEX REBUILD or ALTER INDEX REORGANIZE commands. Azure SQL also provides the sys.dm_db_index_physical_stats dynamic management view, which can be used to monitor the state of your indexes.

In conclusion, managing indexes in large databases is a complex task that requires careful planning and regular maintenance. But with the right strategies and tools, it is possible to maintain efficient and performant indexes even in databases of 5TB or more.

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