Friday, January 11, 2013

HBase: secondary index

As your HBase project moves forward you will likely face a request to search by criteria that is neither included into the primary index nor can be included into it. In other words you will face a problem of fast and efficient search by secondary index. For instance: select all eReaders in a specific price range. In this post, we will review an approach of constructing a secondary index.

As usually, we will work in realm of Surus ORM [1] and Synergy Mapreduce Framework [2], and will start with the definition of a model. For illustration purposes we will use simplified variant of "product" class, that has lowest and highest prices and can only belong to one category. For instance:

ID category priceLowest priceHighest manufacturer
Sony eReader PRST2BC E-READER 8900 12900 SONY

Instances will reside in a table product:

To satisfy our search requests, we would like to get a following structure:
ID products
Sony eReader PRST2BC Kobo ... ...
E-READER { priceLowest : 89000,
priceHighest: 12900,
manufacturer: SONY}
{ ... } { ... }
Here, any search within a specified category would allow us to quickly filter out products in a specific price range or manufacturer.

To create an index as described above, we would need a new model to hold filtration criterias and a mapreduce job to periodically update it.
Secondary index model:

and its corresponding grouping table:

Mapreduce job implies that Job Runner will use product table for source and grouping table for sink. Job's mapper:
and a reducer:
As an alternative to secondary index you can use filtering. For instance SingleColumnValueFilter:
However, SingleColumnValueFilter approach is insufficient for large tables and frequent searches. Stretching it too far will cause performance degradation across the cluster.

To sum it up, secondary indexes are not a trivial, but at the same time - not a paramount of complexity. While designing them, one should look carefully for the filtration criteria and "long-term" perspective.

Hopefully this tutorial would serve you with help.

[1] Surus ORM

[2] Synergy Mapreduce Framework

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