Memory-Optimized Indexing Strategy

Kunal Karoth has some advice for creating memory-optimized indexes:

To further optimize your queries that do point lookups on your memory-optimized table using an equality operator (=), consider using a Hash index. Hash indexes also optimize insert operations and aid database recovery time. As mentioned earlier, a Hash index uses a hash table internally to keep track of the index keys. The hashing function uses all the key(s) specified at the index creation time to create a mapping between the index key column(s) and the corresponding hash bucket. Hence, it is important that you specify all the index key columns that are part of the hash index, during the lookup in your query.

As with any hashing technique, collisions will occur. A hash collision occurs when two or more index keys map to the same hash bucket. In general, having a limited number of collisions is expected and is fine. It is only when the number of collisions become excessive, it may noticeably begin to impact your query performance. Your aim should be to keep the number of collisions as low as possible. You may experience a higher number of collisions either because: –

  • There are many duplicate index key column values in the table and/or

  • The number of hash buckets for your Hash index are under provisioned.

There’s some helpful information here if you are new to In-Memory OLTP.

Related Posts

Unused Indexes Might Not Be

Tara Kizer has a warning for people eager to drop “unused” indexes: About 10 years ago, I decided to drop an unused index on a table that had 2 billion rows. The database was around 7TB in size. We were having storage and performance issues. I thought I could help the system out if I […]

Read More

Hybrid Columnstore And B+ Tree Designs

Adrian Colyer reviews a Microsoft paper on the combination of columnstore and B+ tree indexes on a single table: The authors conducted a series of microbenchmarks as follows: scans with single predicates with varying selectivity to study the trade-off between the range scan of a B+ tree vs a columnstore scan sort and group-by queries […]

Read More

Categories

November 2017
MTWTFSS
« Oct Dec »
 12345
6789101112
13141516171819
20212223242526
27282930