InnoDB Magic

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1. g414-inno Embedded InnoDB, Voldemort, St8, and a Few Other Tidbits Sunny Gleason
2. What’s in this Preso • What is InnoDB? • Relation to MySQL & Other Products • InnoDB Model • g414-inno: a Java Access Library for InnoDB
3. What else is in this Preso • Creating a Voldemort Storage Engine with Embedded InnoDB • St8: A REST-based Storage Server • Faban Benchmark Results
4. What is InnoDB? • High-Performance “guts” of MySQL • Finely Tuned B-Tree Storage Engine • MVCC Transactional Store a la Jim Gray (“Transactional Processing Systems”) • Available Stand-Alone as Embedded InnoDB (stagnant) or HailDB (drizzle)
5. Relation to MySQL • One of many MySQL storage engines • Transactional, in contrast to MYISAM • Well-known, Bullet-Proof Backup, Failure & Recovery Modes • Advanced Buffer Pool Management (adaptive hash index, tunable LRU) • Online Backup Support (Xtrabackup / Hot)
6. Other Products • Tokyo BDB, Oracle BDB & BDB-JE • Schema-Free (No Structure / Data Types) • Lower Concurrency (fewer writers) • Performance Degradation in Larger DBs • (TODO: quantify performance gap - in meantime, see Dynamo & Voldemort)
7. InnoDB Model (Logical) • Database == Tablespace • Tablespace has Table(s) and Log(s) • Table has columns (rich datatypes) • Tables have a PRIMARY clustered index • Tables may have SECONDARY indexes • Row == Tuple • Tuples are stored / clustered by index sort • Secondary index stores full Primary Key
8. InnoDB Model (Txns) • Everything uses a Transaction • Isolation Level: Serialized, Read Committed, Read Uncommitted • Locks: Shared (Read-only), Exclusive (Read/Write) • Cursors provide access to tables: Lookup by index, Iteration / Traversal • Secondary index contains partial Tuples • Secondary cursor can access primary (full tuple)
9. InnoDB Model (Physical) • Tablespace is a collection of pages (16K) • Pages organized as a B-Tree: infimum & supremum keys, pointers to children • Pages contain row or index tuple data, or blob overflow data • Pages written to log first and flushed to tablespace based on ‘sync’ policy
10. Physical Considerations • New pages requested from OS in extend_size increments • OS Assigns space from file system / partition “free list” • Temporal Locality (pages close together) • Spatial Locality / Fragmentation from Updates • Prefer “narrow” rows / indexes: faster scan, keeps working set in-memory • Secondary “covering” indexes can save primary index access
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16. How can we use InnoDB? • Download Embedded InnoDB or HailDB • Use C-API for access to InnoDB tables • Innostore: Erlang library for InnoDB access (from Basho’s Riak NoSQL project) • g414-inno: Open-Source Java access library for Embedded InnoDB
17. g414-inno Foundations • Uses JNA (Java Native Access): Like JNI, but doesn’t provoke (as much) insanity • JNAerate: creates thin Java Class wrapper from a C-based header file (innodb.h) • But, complex C API’s are super ugly in Java • Need to clean that up a bit...
18. g414-inno Library • Provides a more Object-Oriented API to mask all of the JNA “Pointer” madness • Transaction Objects, Cursors, Table Builder, Tuple Builder, Datatype Validation • Java Enum Types for ‘int’ enums in C API • inTransaction() templates (like Spring, JDBI) • Contains sanity checks to prevent common errors (mostly C API order of operations)
19. Use Case: Voldemort • Voldemort: High-Performance Key-Value Store (Amazon Dynamo clone) • Nokia: good results with Voldemort on MySQL with InnoDB • Typical features of DB (network connectivity, SQL language) not really necessary • Thought: why bother with DB layer? The g414-inno project is born ...
20. Voldemort Storage Engines • Trivial to integrate new persistence mechanisms with Voldemort • 2 Classes: Config & Storage Engine • Trivial InnoDB Table: key_ VARBINARY(200) NOT NULL version_ VARBINARY(200) NOT NULL value_ BLOB PRIMARY KEY (key_, version_) • 3 Operations: put(k, v), get(k), delete(k) • Complication: k is Versioned<Key>
21. V Storage Engine: put • put(byte[] key, byte[] version, byte[] value) • Start transaction, open table cursor • Create search tuple for key • Cursor.find(key) • Foreach row matching key if row.version is below, delete row if row.version is above, throw exception • Cursor.insert(key, version, value)
22. V Storage Engine: get • get(byte[] key, byte[] version) • Start transaction, open table cursor • Create search tuple for key • Cursor.find(key) • Foreach row matching key add to results • Return results
23. V Storage Engine: delete • delete(byte[] key) • Start transaction, open table cursor • Create search tuple for key • Cursor.find(key) • Foreach row matching key delete row
24. V Storage Engine: TODO • Perform Benchmarks (in EC2, local) • Tuning / Optimization • Clarify licenses (GPLv2 + Apache == ouch) • Organize & streamline distribution
25. St8 • Simple, Open Source REST-based Storage Server • Wraps InnoDB with thin “but pleasant” HTTP API • Custom Tables using JSON table definitions • Natural, JSON-based access to tables: CRUD, Index- based Query & Iteration • Under the hood: Jetty, Jersey, Guice, Jackson, g414- inno, Embedded InnoDB
26. St8 Table Def { "columns":[ {"name":"key1","type":"INT","length":4}, {"name":"key2","type":"VARCHAR","length":50}, {"name":"val","type":"BLOB","length":0} ], "indexes":[ { "name":"PRIMARY", "clustered":true,"unique":true, "indexColumns":[{"name":"key1"}] }, { "name":"key2", "clustered":false,"unique":false, "indexColumns":[{"name":"key2"}] } ] }
27. St8 Interface • Operations for Table Management: create, describe, delete, truncate • Operations for Data Management: Create, Retrieve, Update, Delete • Influences g414-inno design: template methods for inTransaction(), insert, update, insertOrUpdate, delete, load • Coming Soon: Query & Iteration APIs
28. St8: Sample Requests SIMPLE GET: curl "http://localhost:8080/d/atable;key1=123" INSERT: curl -X PUT "http://localhost:8080/d/atable;key1=123;key2=ABC;val=AVERYLONGDATA" UPDATE: curl -X POST "http://localhost:8080/d/atable;key1=123;key2=CDE;val=NEWDATA" DELETE: curl -X DELETE "http://localhost:8080/d/atable;key1=123"
29. g414-inno: Faban Benchmark • Row: 4-byte Key, 4096-byte value • Insert Sequential, Random • Single disk, 3-disk RAID 0, SSD • TODO: Concurrent Benchmarks, Mixed Read/Write
30. Benchmark Results 0 5 10 15 20 InsertSeq InsertRnd SelectRnd Embedded InnoDB Latency (ms) Single Disk (OS X 1) 3-Disk Raid 0 (OS X 1) SSD (OS X 2) Single-Threaded Benchmarks InsertSeq InsertRnd SelectRnd Single Disk (OS X 1) 9.0 9.3 16 3-Disk Raid 0 (OS X 1) 0.47 1.4 5.2 SSD (OS X 2) 0.51 1.2 0.71
31. Next Steps / Future Work • Finish St8: Queries & Iteration, Benchmark • Package / Qualify Voldemort Storage Engine • Integrate with Xtrabackup (hot backup) • Integrate with Sqoop (hadoop export) • Explore more advanced App-Level Replication Support
32. Questions? • Thank you for listening!
33. References / More Info • Embedded InnoDB, HailDB (drizzle) • InnoDB Performance • GitHub: g414-inno, st8, voldemort, xfaban • Java Native Access (JNA) • Tokyo BDB, Oracle BDB & BDB-JE • Amazon Dynamo; Voldemort Project