Hadoop at Lookout
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This document summarizes Yash Ranadive's talk on Hadoop at Lookout. It discusses how Lookout uses analytics to make smartphones and tablets secure, their data analytics team structure, and their event ingestion pipelines using Storm and Hadoop. The key parts of their architecture include ingesting event data through Storm topologies into Hadoop, running queries on Hive, and using tools like Tableau, Hue, and custom apps for reporting and ad hoc querying.
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- 2. AGENDA What we do @Lookout Analytics Architecture Event Ingestion Pipelines Storm Questions
- 3. BIO Data Engineer at Lookout, started 2013 Previously at Demandbase, Project Perf. Corp. 6 years of Data Engineering From Mumbai, India etl.svbtle.com
- 4. WHAT WE DO @LOOKOUT
- 5. MAKE SMARTPHONES AND TABLETS SECURE & TRUSTWORTHY FOR INDIVIDUALS AND ORGANIZATIONS
- 8. WHO WE SERVE Product Managers Software Developers Marketing Security Research
- 9. DATA ANALYTICS TEAM 7 Analysts/Scientists Questions they answer How many users located their phone yesterday? How many users were billed for AT&T?
- 10. DATA ANALYTICS TEAM 3 Data Engineers Build and maintain pipelines for Analytics and ad-hoc querying
- 13. REPORTING Tableau Dashboards - Retentions, Activations, etc. Email reports Custom email reports (Ruby)
- 14. ADHOC QUERYING Hive CLI - Command-line interface to Hive Hue - Toad style GUI for ad hoc queries on Hive R Studio - Statistical analysis Shiny - Reporting/Querying tool based on R Sparkle Pony(Homegrown Ruby app) - MySQL Querying for stakeholders Hadoop File System Browser
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- 17. PIPELINES
- 18. STORM
- 19. STORM Apache Storm is a distributed realtime computation system. It can be used with any programming language.
- 20. TOPOLOGY DESIGN
- 21. NIMBUS AND SUPERVISOR A storm cluster has One Nimbus node which is the master A set of Supervisor nodes which are the workers
- 22. TOPOLOGY CONSISTS OF SPOUTS AND BOLTS
- 24. LANDING DATA IN HADOOP Topologies write data to a landing directory in Hadoop using HDFS Bolt Directories are rotated depending on latency requirements of downstream reports Directories are moved to location of the table in Hive
- 27. DEPLOYMENT Storm topologies are jars that can be submitted to Storm Nimbus storm jar path/to/allmycode.jar org.MyTopologyClass arg1 arg2
- 28. DEPLOYMENT Configuration is stored in shell scripts that launch topologies storm jar /topolgoies/data-storm-0.0.3-SNAPSHOT.jar com.lookout.data.topology.KafkaToHdfsTopology -topologyname kafka-hdfs -nimbushost dw-storm2 -topologymaxtaskparallelism 1 -D hdfs.sync.tuple.count=500 -D hdfs.file.rotation.seconds=3600 -D hdfs.landing.directory=/user/hive/warehouse/staging.db/locate_events -D hdfs.destination.directory=/user/hive/warehouse/realdb.db/locate_events -D hdfs.filesystem.url=hdfs://hadoop-cluster-01:8020/ -D kafka.zookeeper.hosts=zk1:2181,zk2:2181,zk3:2181 -D kafka.topic=locate_event -D statsd.host=statsdhost
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- 32. GRAPHITE
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