Introduction to Apache Accumulo

1. Introduction to Apache AccumuloBoulder/Denver BigData Meetup - March 21,2012Jared Winick@jaredwinick

2. Accumulo /əˈkjuˈmj ʊ/ ʊˈlo1. Sorted, distributed key/value store with cell-based access control and customizable server-side processing

3. http://yourmotivational.com/uploads/8604.jpg

4. Annotation AddedJeff Dean: Designs, Lessons and Advice from Building Large Distributed Systemshttp://www.cs.cornell.edu/projects/ladis2009/talks/dean-keynote-ladis2009.pdf

5. Enables interactive access to… Trillions of records petabytes of indexed data across 100s-1000s of servers

6. Short Accumulo History Lesson http://www.flickr.com/photos/mr_t_in_dc/4249886990/sizes/l/in/photostream/

7. 2006

8. 2008http://upload.wikimedia.org/wikipedia/commons/8/84/National_Security_Agency_headquarters%2C_Fort_Meade%2C_Maryland.jpg

9. 2011

10. 2012

11. Uses of BigTable and Kin (BigTable) (HBase)•Google Analytics1 •Messages3,4,6•Crawl1 •Insights5,6•AppEngine Datastore2•Many more1 (Cassandra) (Accumulo) •Rainbird (realtime analytics)7 •???1.) http://static.googleusercontent.com/external_content/untrusted_dlcp/research.google.com/en/us/archive/bigtable-osdi06.pdf2.) http://code.google.com/appengine/articles/storage_breakdown.html3.) http://www.facebook.com/note.php?note_id=4549916089194.) http://mvdirona.com/jrh/TalksAndPapers/KannanMuthukkaruppan_StorageInfraBehindMessages.pdf5.) http://www.facebook.com/note.php?note_id=101501039002589206.) http://borthakur.com/ftp/SIGMODRealtimeHadoopPresentation.pdf7.) http://www.slideshare.net/kevinweil/rainbird-realtime-analytics-at-twitter-strata-2011

13. Multi-dimension Key Key Column Value Row ID Timestamp Family Qualifier Visibilityhttp://incubator.apache.org/accumulo/user_manual_1.4-incubating/Accumulo_Design.html

14. Keys Sorted LexicographicallyRow ID, Column Family, Column Qualifier, Column Visibility, Timestamp Everything is a byte[] except the Timestamp which is a long

15. Physical Layout Key ValueRow ID Col Fam Col Qual Col Vis Time Value Alice properties age public March 2011 31 Alice properties phone private Feb 2011 555-1234 Alice purchases Xbox public Feb 2011 $299 Bob properties phone private March 2011 555-4321 Bob purchases iPhone Public Feb 2011 $399

16. Queries •By exact Key or range of Keys •Data is always returned in sorted orderQuery Requirements Drive Data Model Design

17. http://incubator.apache.org/accumulo/user_manual_1.4-incubating/Accumulo_Design.html

18. Hadoop Clients MapReduce Read/ Analytics Write Accumulo Configuration/ Storage StateHadoop HDFS Zookeeper

19. Table Tablets Accumulo… Tablet Server … … Tablet Server … ... … Tablet Server … Master Data Node Data Node ... Data Node Name Node Hadoop HDFS

20. Table Tablet Server Failure Tablets 1.) Detect FailureAccumulo Tablet Server Tablet Server ... Tablet Server Master 2.) Reassign Data Node Data Node ... Data Node Name Node Hadoop HDFS

21. Writes Write- Ahead Accumulo Log (WAL) Tablet Server 1 Tablet 2 MemTableClient Data Node ... Data Node Data Node Hadoop HDFS

22. Writes Write- Ahead Accumulo Log (WAL) Tablet Server 1 Tablet 2 MemTableClient 3 File 1 Data Node ... Data Node Data Node Hadoop HDFS

23. Compactions Minor MajorThe process of flushing The process ofa MemTable of a Tablet combining multiple filesto a single file in HDFS into a single file

24. Tablet Splits• Tablets are split when they reach a max size• Always split on row boundary• Master assigns a split Tablet to another Tablet server (no data is moved!)

25. Reads Accumulo Tablet Server Tablet MemTableClient File 1 File 1

27. Iterators: Server-side programminghttp://wiki.eeng.dcu.ie/ee557/287-EE/version/default/part/ImageData/data/server-side_intro.gif

28. IteratorsCan be run at: Can do things like:•Scan Time •Aggregation (Combiners)•Minor Compaction •Age-Off•Major Compaction •Filtering (access control) •TransformationPush Processing to the Data

30. Access Control• Every key-value has a visibility label• Label is defined with boolean operators• Label is arbitrary and ad-hoc Public Private | Admin Finance | (HR & Manager)• Authorizations presented at scan time• Data is filtered out automatically by system- level Iterator

31. Access Control – Typical Architecture Trusted Zone 6.) Return Data 5.) Return Visible Data Web Server Accumulo1.) Pass Credentials 4.) Proxy Authorization 3.) Return Authorizations 2.) Lookup User Enterprise Identity Management

32. Access Control – Typical Architecture Trusted Zone Accumulo 6.) Return [6,8] 5.) Return [6,8] SECRET&PROJECT X, 6 Web Server SECRET&PROJECT Y, 8 1.) PKI Cert 4.) Proxy Bob’s Auths SECRET&PROJECT Z, 3Bob 3.) Auths:[SECRET, UNCLASSIFIED, 2.) Lookup PROJECT X, PROJECT Y] Bob Enterprise Identity Management

33. Demo

34. Application RequirementsBuild an application to analyze trends in Twittermessages.•Query for word/phrase and view real-time activityin a time series graph•View at different time ranges (1 day, 7 days, 30days, etc)•Allow multiple query terms to compare activity (ex.Breakfast,Lunch)•Automatically extract daily trends for the user

35. Demo Setup/Data• Twitter Streaming API• US country codes only messages• 1,2,3-grams built• Data since Dec 24 – Live• Running on average workstation, 1 SATA disk, 6 GB memory.• 72GB, 2.6 billion entries and counting

36. Data Model• Tweets table – Row ID: n-gram – Column Family: Date Granularity (DAY, HOUR) – Column Qual: Date Value – Value: Count – SummingCombiner (Iterator) used to update Count Row ID Col Fam Col Qual Value breakfast DAY 20120318 31 breakfast DAY 20120319 56 … … … … lunch HOUR 2012031801 3 lunch HOUR 2012031802 4

37. Data Model• Trends table – Row ID: (Date Granularity + Date Value) – Column Family: (Integer.MAX_VALUE – trendScore) – Column Qual: n-gram – Value: [] Row ID Col Fam Col Qual ValueDAY:20120318 2147483145 churchDAY:20120318 2147483316 hangover … … … …DAY:20120319 2147476521 the broncosDAY:20120319 2147477704 tim tebow

38. MapReduce Analytics• Utilize MapReduce for building trends• AccumuloInputFormat reads from tweets table• AccumuloOutputFormat writes to trends table• AccumuloStorage LoadFunc for Pig available on github

39. Summary•Accumulo exploits locality to enableinteractive access to huge data sets whileadding cell-level access control and server-side programming•Nothing in life is free. Accumulo comes withthe complexity and responsibility ofmanaging a distributed system and designingindexes on your data

40. References• Documentation, Mailing Lists, Linkshttp://incubator.apache.org/accumulo/• HBase Shootouthttp://www.slideshare.net/cloudera/h-base-and-accumulo-todd-lipcom-jan-25-2012• Trendulohttps://github.com/jaredwinick/trendulo