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Hadoop For Enterprises
- 1. Hadoop for Enterprise rev 7 Rajesh Nadipalli Mar 2012 [email protected]
- 2. Hadoop getting attention • Feb 2012: Microsoft, Hortonworks in partnership to develop Excel plug-in for Hadoop • Jan 2012: Oracle announces Big Data Appliance with Cloudera’s Hadoop distribution • Dec 2011: EMC released Unified Analytics Platform which includes Greenplum Apache Hadoop distribution • Oct 2011: Microsoft plans to add Hadoop support to SQL server 2012 • May 2010: IBM introduces Hadoop based InfoSphereBigInsights [email protected]
- 3. In this Presentation… Big Data – Big Opportunities Hadoop for Enterprise – Reference Arch Map Reduce Overview Hive References [email protected]
- 4. BIG DATA –BIG OPPORTUNITIES [email protected]
- 5. Big Data -Business Opportunity Enterprises today are challenged with.. Exponential data growth Complex data needs- structured & unstructured Real time insights with key indicators Heterogeneous environment: private and public clouds Tighter budgets and the need to do more with less Traditional relational databases are not able to scale and meet these challenges [email protected]
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- 7. Why Hadoop? Hadoop provides… Distributed File System Parallel computing across several nodes Support for structured and un-structured content Fault tolerance and linear scalability Open source under Apache foundation Increasing support from vendors Key Philosophy: “moving compute is cheaper than moving data” Forrester regards Hadoop as the nucleus of the next-generation EDW in the cloud. [email protected]
- 8. Some users ofHadoop… http://wiki.apache.org/hadoop/PoweredBy • Use Hadoop to store copies of internal log and dimension data sources and use it as a source for reporting/analytics and machine learning. • Currently we have 2 major clusters: A 1100-machine cluster with 8800 cores and about 12 PB raw storage. A 300-machine cluster with 2400 cores and about 3 PB raw storage. • Each (commodity) node has 8 cores and 12 TB of storage. • Hadoop used to analyze the log of search and do some mining work on web page database • We handle about 3000TB per week Our clusters vary from 10 to 500 nodes • 532 nodes cluster (8 * 532 cores, 5.3PB). • Heavy usage of Java MapReduce, Pig, Hive, HBase • Using it for search optimization and Research •5 machine cluster (8 cores/machine, 5TB/machine storage) •Existing 19 virtual machine cluster (2 cores/machine 30TB storage •Predominantly Hive and Streaming API based jobs (~20,000 jobs a week) •Daily batch ETL; Log analysis; Data mining; Machine learning [email protected]
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- 10. Hadoop for Enterprise– Technology Stack User Experience Ad-hoc Notifications Embedded Analytics queries /Alerts Search Data Access Excel R (Rhipe, Hive Pig Datameer RBits) Zookeeper (Orchestration, Quorum) Pentaho (Scheduling, Integrations) Data Processing Mapreduce Hadoop Data Store Hbase (NOSQL DB) HDFS Sqoop Data Sources Application Database Log RSS Cloud Others s (internal) s Files Feeds [email protected]
- 11. Hadoop for BI– Reference Architecture Data Hadoop Distributed Computing Enterprise Apps Environment Dashboards RDBMS Excel M XML A N-Node JSON P scalable cluster ERP, Enterprise Apps Binary R E CSV D U Log C Import RDBM E S Java Hadoop File Objects System (HDFS) [email protected]
- 12. http://www.oracle.com/technetwork/database/focus-areas/bi-datawarehousing/wp-big-data-with-oracle- 521209.pdf?ssSourceSiteId=ocomen Oracle’s Big Data Solution • Oracle sees Hadoop is good for unstructured sourcing and map reduce. • It recommends to use Oracle database for the final analyze stage • Oracle Data Integrator can make Hive queries (ETL) • Oracle has a wrapper on top of sqoop which is called Oraoop (see references) [email protected]
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- 14. Hadoop Mapreduce Overview Map Reduce Process Node 1 010101010101010101010 Node 1 10 222222222222222222 010101010101010101010 Map 3333333333333333333 10 3333333333333333333 DATA (from HDFS) 010101010101010101010 10 RESULTS 01010101010101010101010 01010101010101010101010 Node 2 2222222222222222 01010101010101010101010 22 01010101010101010101010 010101010101010101010 Node 2 3333333333333333 01010101010101010101010 Reduc Split 10 33 01010101010101010101010 2222222222222222222 e 010101010101010101010 4444444444444444 01010101010101010101010 Map 3333333333333333333 10 44 01010101010101010101010 4444444444444444444 010101010101010101010 01010101010101010101010 10 01010101010101010101010 01010101010101010101010 01010101010101010101010 Node 3 Node 3 010101010101010101010 10 010101010101010101010 222222222222222222 10 Map 3333333333333333333 010101010101010101010 3333333333333333333 10 [email protected]
- 15. Map Reduce Tips The first step is to understand what data you have, and how to feed it into the Hadoop distributed computing environment. Using distributed applications, provide analytics of the massive data sets, while simultaneously enabling the surfacing of opportunities. Hadoop stores your information for future queries, enhancing the exploratory capabilities (as well as historical reference) of your data. [email protected]
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- 17. HDFS Distributed file system consisting of ◦ One single node is called “Namenode” and has metadata ◦ Several “Datanodes” Designed to run on commodity hardware Data gets imported as blocks (64 MB) These Blocks are replicated (typically 3 copies) to protect for hardware failures Access via Java API’s or hadoop command line ($hadoop fs…) [email protected]
- 18. http://hadoop.apache.org/common/docs/current/hdfs_design. html HDFS architecture Hadoop next revision has a failover Namenode called “Avatar” [email protected]
- 19. HBase Distributed, column-oriented database (NoSQL) Failure-tolerant Low latency HDFS aware Access via Java APIs or REST APIs It is not a replacement for RDBMS Recommended to use Hbase when ◦ Data is searched by key (or range) ◦ Data does not conform to a schema (for instance if you have attributes that change by record). [email protected]
- 20. Hbase Architecture Zookeeper Avatar Hbase (Failover of Master master) Region Region Region Region Server Server Server Server Zookeeper maintains quorum and knows which server is the master Master keeps track of regions and region servers Region servers store table regions [email protected]
- 21. Hbase Column Storage Hbasestores data like tags for a key; for example: Row Column Column Cell Family Cast Cast:Actor1 Harrison Ford Star Wars Cast:Actor2 Carrie Fisher Reviews Review: IMDB Review URL Review: ET Review URL2 [email protected]
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- 23. Hive Overview Datawarehouse software built on top of Hadoop HiveQL provides a SQL like interface and performs a map reduce job Provides structure to HDFS data similar to Oracle External table [email protected]
- 24. Hive Architecture Hive CLI Browse Query Hive QL Hive Parser Metastore Execution SerDe (Map Reduce) HDFS [email protected]
- 25. Pig Overview Pigis a layer on top of map-reduce for statisticians (programmers) It provides several standard operators: join, order by etc It allows user defined functions to be included. Java or phyton supported for UDF’s [email protected]
- 26. http://www.datameer.com/ Datameer Overview Key philosophy:Business users understand Excel; let them do the grouping, sorting, filtering, aggregates Key Steps: Datameer’s source is a mapreduce output. Datameer takes a quick sample of 5000 records. The end user is next presented an Excel like interface on top of this 5000 records. This is where the end users can define their filters, formula, grouping, aggregations, joins across sheets (even join hadoop data with data from a relational database table) Once the end user has defined what they want as the end result, they can submit a job to run on the complete dataset. Datameer will then build the necessary map reduce jobs and run it on the complete data set. Next the user gets the results and can build charts, tables etc – all on the browser [email protected]
- 27. http://www.informationweek.com/news/software/info_management/232601675?cid=RSSfeed_IWK_News Excel Integration Microsoft announcedExcel integration with Hadoop (Feb 2012) with HortonWorks Key Highlights: Microsoft &Hortonworks will deliver a Hive ODBC driver that will enable integration with Excel Microsoft’s PowerPivot in-memory plug-in for Excel will handle larger data sets There is also a plan for Javascript framework for Hadoop enabling Ajax like iterative [email protected]
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- 29. Pentaho Data Integration Pentaho is considered as “strong performer” by Forrestor (Feb 2012) It makes building MapReduce easy via it’s Data Integration IDE. It can read/write to HDFS, run map reduce and Pig scripts The IDE has several standard connectors, transformation, and allows custom java code http://www.pentaho.com/big-data/ [email protected]
- 30. http://www.youtube.com/watch?v=KZe1UugxXcs&feature=player_emb edded Pentaho Data Integration Build Reducer 2 1 Build Mapper Run Map 3 Reduce [email protected]
- 31. Talend - ETL Talend is another ETL development, scheduling and monitoring tool It supports HDFS, Pig, Hive, Sqoop http://www.talend.com/products-big- data/ [email protected]
- 32. Talend ETL –with Hadoop • Can invoke Hadoopcalls (generates Hive queries) • See right slide “Processing” [email protected]
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- 34. User Experience This layerof stack is generally custom development. However some tools that work with Hadoop are: Tableau for data analysis & visualizations SAS Enterprise Miner IBM BigInsights [email protected]
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- 36. References http://hadoop.apache.org/ http://www.cloudera.com/ http://www-01.ibm.com/software/data/bigdata/ http://www.cs.duke.edu/starfish/index.html http://www.michael-noll.com/tutorials/running-hadoop-on-ubuntu-linux-single- node-cluster/ http://karmasphere.com/Download/karmasphere-studio-community-virtual- appliance-for-ibm.html http://www.slideshare.net/zshao/hive-data-warehousing-analytics-on-hadoop- presentation http://www.slideshare.net/trihug/trihug-november-pig-talk-by-alan- gates?from=ss_embed http://www.trihug.org/ http://www.cisco.com/en/US/prod/collateral/switches/ps9441/ps9670/white_paper _c11-690561.html http://www.cloudera.com/wp-content/uploads/2011/01/oraoopuserguide-With- OraHive.pdf [email protected]
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- 39. MAP-R No singlepoint of failure of name node Performance improvements (5 times faster than HDFS) Snapshots, Multi-site copies They have separate Mapreduce (extended mapreduce) MapR is 8K blocks instead of 64MB block size of HDFS [email protected]
- 40. Open Topics –why there is adoption issue Security – no concept of roles Backup, Recovery ACID not supported [email protected]
- 41. Thank You tomy viewers [email protected]
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Editor's Notes
- #3 (http://www.zdnet.com/blog/big-data/hadoop-20-mapreduce-in-its-place-hdfs-all-grown-up/267http://www.informationweek.com/news/software/info_management/231900633http://www.informationweek.com/news/software/info_management/232400021http://www.informationweek.com/news/software/info_management/232300181http://www-01.ibm.com/software/data/infosphere/biginsights/basic.htmlhttp://www.informationweek.com/news/galleries/software/enterprise_apps/232500290?pgno=1
- #6 http://www.informationweek.com/news/software/bi/229900002?cid=RSSfeed_IWK_News
- #7 http://www.informationweek.com/news/software/bi/229900002?cid=RSSfeed_IWK_News
- #8 Hadoop implements the core features that are at the heart of most modern EDWs: cloud-facing architectures, MPP, in-database analytics, mixed workload management, and a hybrid storage layer
- #9 http://wiki.apache.org/hadoop/PoweredBy
- #11 HBase is a full-fledged database (albeit not relational) which uses HDFS as storage. This means you can run interactive queries and updates on your dataset. Sqoop takes data from any DB that supports JDBC and moves it into HDFSIf you haven’t already, check out Toad® for Cloud Databases, our free, fully functional, commercial-grade cloud solution. With Toad for Cloud Databases, you can easily generate queries, migrate, browse, and edit data, as well as create reports and tables – all in a familiar SQL view. Finally, everyone can experience the productivity gains and cost benefits of NoSQL and big data – without the headachesToad for Cloud Databases provides unrivaled support for Apache Hive, Apache HBase, Apache Cassandra, MongoDB, Amazon SimpleDB, Microsoft Azure Table Services, Microsoft SQL Azure, and all open database connectivity (ODBC)-enabled relational databases (including Oracle, SQL Server, MySQL, DB2, and others)
- #12 Netflix uses similar reference architecture for movie recommendations. Hadoop is not suited for low latency. Facebook does use Hbase for messaging which is close to a real time functionality
- #21 http://facility9.com/nosql/glossary/
- #30 Weka read this… it is similar… Mahoot is AI…