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Secondary Indexing

Jesse Yates Salesforce.com. Secondary Indexing. t he discussion so far…. 9/11/12 HBase Pow -wow. What is it?. Problem. HBase rows are multi-dimensional Only sorted on the row key How do you efficiently lookup deeper into the row key?. Example.

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Secondary Indexing

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  1. Jesse Yates Salesforce.com Secondary Indexing the discussion so far…. 9/11/12 HBase Pow-wow

  2. What is it?

  3. Problem • HBase rows are multi-dimensional • Only sorted on the row key • How do you efficiently lookup deeper into the row key?

  4. Example How do we find all people with the last name ‘Ruth’? Full table scan!

  5. Indexing! • Store the property we need to search for as the primary key • pointer back to the primary row • fast lookup - O(lg(n))

  6. Use Cases • Point lookups • Volume of data influences usefulness of index • Let user decide if they need to use an index • Scan lookup • WHERE age > 16

  7. Implementations

  8. Omid Full transactional support Centralized oracle

  9. Lily WAL implementation on top of HBase 100-500 writes/sec

  10. Percolator Full transactions Distributed, optimistic locking ~10 sec latencies possible

  11. Culvert Async Dead project, incomplete

  12. http://jyates.github.com/2012/07/09/consistent-enough-secondary-indexes.htmlhttp://jyates.github.com/2012/07/09/consistent-enough-secondary-indexes.html Client-side coordinated index Use timestamps to coordinate Not yet implemented

  13. Trend Micro Implementation Still just POC ???

  14. Solr/Lucene Standard Lucene library bolted on HBase Not commonly used Lots of formats/codecs already written

  15. Considerations for HBase What do we need to do?

  16. Built-in vs. external library vs. semi-supported (e.g. security)

  17. Which should I use?? • HBase experts write a single ‘right’ impl • Officially endorse a ‘correct’ version • What changes do we need to make • How close to the core is the project • Written in everywhere • hbase-index module • External library

  18. Async vs. Synchronous vs. Transactional

  19. Key Observation “Secondary indexing is inherently an easier problem than full transactions… secondary index updates are idempotent.” - Lars Hofhansl

  20. Async vs. Synchronous vs.Transactional • We don’t need full transactions • Transactions are slow • Transactions fail with increasing probability as number of servers increases • Optionally async or sync • Async • Inherently ‘dirty’ index • How does index cleanup work? • Inherently different for each type

  21. Locality

  22. Where’s my data? • Extra columns vs. index table • HBase Region-pinning • Has to be best-effort or will decrease availability • Helps minimize RPC overhead • Cross-table region-pinning • Needs a coprocessor hook to be useful • HDFS block allocation • Keep index and data blocks on same HDFS node

  23. Index Cardinality

  24. How much data are we talking? “Seems like there are 3 categories of sparseness: • sparse indexes (like ipAddress) where a per-table approach is more efficient for reads • dense indexes (like eventType) where there are likely values of every index key on each region • very dense indexes (like male/female) where you should just be doing a table scan anyway” - Matt Corgan (9/10/12)

  25. Impact on implementation • Need a lot of knowledge of data to pick the right kind of index • User knows their data, let them do the hard work of picking indexes

  26. Pluggability

  27. Everyone’s got an impl already • We need to make HBase flexible enough to support (most) current indexing formats with minimal overhead for switching • Lucene style Codec/CodecProvider?

  28. Client-interface

  29. What should it look like? • Minimal changes to the top-level interfaces • Add a single new flag? • Configuration based? • Enough that the user gets to be smart about what should be used • We can’t get all cases right – just provide building blocks • Automatically use an index? • Scanner/Filter style use?

  30. Properties for the client • Should the user even see the index lookups? • ACID? • Ordering of results? • Support the current sorted order? • Batch lookup? • Implications on current features • Replication • splitting

  31. Schema(less) • Schema enforced? • Rigid usage of index matching an expected schema? • Schema table? Reserved schema columns?.META.? • Schema-less • Let the user apply whatever they think and use only what actually works • Best-effort • Use client-hinted schema and try to apply all the known indexes

  32. My random thoughts…. • Client-side managed indexes are efficient • Minimal RPC overhead • Cleanup is async to client and rarely misses • Solves the cross-region/server problem • Region-pinning is a nice-to-have optimization • Scales without concern for locality • Flexible enough to support custom codecs • Can be built to provide server-side optimizations • Locality aware indexes to minimize RPCs

  33. Discussion!

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