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Introducing TokuMX - MongoDB with Fractal Tree Indexing
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Introducing TokuMX - MongoDB with Fractal Tree Indexing


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Lighting Talk on TokuMX from MongoDB New York User Group 7/16/2013. …

Lighting Talk on TokuMX from MongoDB New York User Group 7/16/2013.

TokuMX integrates fractal tree indexes into MongoDB. Fractal tree indexes are the technology behind the TokuDB storage engine for MySQL. The big benefits:
- reduced I/O utilization on writes for large data
- compression
- faster and more indexing
- no fragmentation (no compact)

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  • 1. Introducing TokuMX Fractal Tree Indexing with MongoDB Zardosht Kasheff @zkasheff @tokutek
  • 2. What is TokuMX? • TokuMX = MongoDB with improved storage • Drop in replacement for MongoDB v2.2 applications (including sharding and replication) o Same data model o Same query language o Drivers just work • Open source
  • 3. TokuMX Benefits • Improved write performance on large data o Much faster on data > RAM o Significantly reduced I/O o Don't need to keep working set in RAM o Maintaining indexes uses less resources • Compression! (up to 10x) • No fragmentation (Deprecated compact!) • Transactions (MVCC + multi-statement) Bottom line: TokuMX makes MongoDB applications stable and fast for large databases.
  • 4. TokuMX comes from TokuDB TokuMX v. 1.0: • Performance • Compression • No fragmentation (no compact) • Transactions TokuDB v. 7.0: • Performance • Compression • No fragmentation (no optimize table) • Agility (online schema changes) TokuMX uses the same core storage code as TokuDB for MySQL. This base provides the general improvements.
  • 5. TokuMX: How? Built a storage core from the ground up, with Fractal Tree indexes, a data structure designed with large data in mind. Key attributes: • Buffers usedto batch up writes, so write I/O is drastically reduced • large blocks of data, so compressionis great • large blocks prevent fragmentation
  • 6. TokuDB Customer case • One of the leading partners of the software, movie and music industry. • Traces copyright infringements and illegal file sharing in P2P networks. • logs IP addresses while also performing a connect to each peer. Fetch data to match it to the copyrighted material for proof of copyright violation. • Ingest large amount of logging information each hour for parallel processing and storage
  • 7. TokuDB Customer case Translation: • Needed indexes on data > RAM to query the data in a variety of ways • Needed compression so that they could store larger volumes of data on a single server
  • 8. TokuDB Customer case Results: • Dramatic I/O reduction • over 3X compression • downtime periods previously spent running "optimize table" eliminated
  • 9. TokuDB: compression Levels of compression depend on how naturally compressible your data is. 9x compression 7x compression
  • 10. TokuMX • • For evaluations or enterprise support: We’re hiring: Senior QA engineer, Tech Support engineer,, @zkasheff on twitter