Apache Falcon is a data management platform for Hadoop that provides data processing, coordination of data pipelines, lifecycle management, and data discovery. It allows users to quickly configure data and processing tasks on Hadoop clusters. Falcon provides services for data relays, retention, replication, acquisition, and enables the holistic declaration of data pipelines and their dependencies. It also supports monitoring of data availability and processing through alerts and dashboards.

1. Apache Falcon
Data Management Platform for Hadoop

4. ●Ajay Yadava
● Committer, Apache Falcon
● Lead - Apache Falcon @ Inmobi
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5. What is Apache Falcon?
Falcon is a data processing and management solution for Hadoop
designed for data motion, coordination of data pipelines, lifecycle
management, and data discovery. Falcon enables end consumers to
quickly onboard their data and its associated processing and
management tasks on Hadoop clusters.
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7. Core Services
Core
Services
Process
Relays
Late
Data
Manage
ment
Retentio
n
Replicati
on
Acquisiti
on
Operabili
ty
Holistic
declarati
on of
intent
Anonymi
zation
Lineage
SLA

8. Life of Byte
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9. Data Relays
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10. Data Retention as a service

11. Late Data Management

12. Data Replication as a service

13. Data Acquisition As Service

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15. Holistic Declaration of Intent

16. Operability – Dashboard

17. Overview
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18. Entity Dependency Graph
Cluster
Feed Process
depends
depends
depends

19. Cluster specification
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<cluster colo="SF-datacenter" description="" name="prod-cluster" xmlns="uri:falcon:cluster:0.1">
<interfaces>
<interface type="readonly" endpoint="hftp://nn:50070" version="1.1.2"/>
<interface type="write" endpoint="hdfs://nn:8020" version="1.1.2"/>
<interface type="execute" endpoint="rm:8050" version="1.1.2"/>
<interface type="workflow" endpoint="http://oozie:41000/oozie/" version="4.0.0"/>
<interface type="registry" endpoint="http://oozie:41000/oozie/" version="4.0.0"/>
<interface type="messaging" endpoint="tcp://:61616?daemon=true" version="5.4.3"/>
</interfaces>
<locations>
<location name="staging" path="/projects/falcon/staging"/> <!--mandatory-->
<location name="temp" path="/projects/falcon/tmp"/> <!--optional-->
<location name="working" path="/projects/falcon/working"/> <!--optional-->
</locations>
</cluster>
Used by distcp for replication Writing to HDFS
Used to submit processes as MR
Submit oozie jobs
Used for alerts
HDFS directories used by Falcon
Hive metastore to
register/deregister partitions & get
data availability events

20. Feed specification
<feed description="enhanced clicks replication feed" name="repl-feed" xmlns="uri:falcon:feed:0.1">
<frequency>minutes(5)</frequency>
<late-arrival cut-off="hours(1)"/>
<sla slaLow="hours(2)" slaHigh="hours(3)"/>
<clusters>
<cluster name="primary" type="source">
<validity start="2013-01-01T00:00Z" end="2030-01-01T00:00Z"/>
<retention limit="days(2)" action="delete"/>
</cluster>
<cluster name="secondary" type="target">
<validity start="2013-11-15T00:00Z" end="2030-01-01T00:00Z"/>
<retention limit="days(2)" action="delete"/>
<locations>
<location type="data" path="/data/clicks/repl-enhanced/${YEAR}/${MONTH}/${DAY}/${HOUR}/${MINUTE}"/>
</locations>
</cluster>
</clusters>
<locations>
<location type="data" path="/data/clicks/enhanced/${YEAR}/${MONTH}/${DAY}/${HOUR}/${MINUTE}"/>
</locations>
<ACL owner="testuser-ut-user" group="group" permission="0x644"/>
</feed>
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Frequency
Location
SLA Monitoring
Data Retention
Data Replication

21. Process specification
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<process name="clicks-hourly" xmlns="uri:falcon:process:0.1">
<clusters>
<cluster name="corp">
<validity start="2011-11-02T00:00Z" end="2011-12-30T00:00Z"/>
</cluster>
<parallel>1</parallel>
<order>LIFO</order>
<frequency>hours(1)</frequency>
<inputs>
<input name="click" feed="clicks-enhanced" start="yesterday(0,0)" end="latest(0)" partition="*/US"/>
</inputs>
<outputs>
<output name="clicksummary" feed="click-hourly" instance="today(0,0)"/>
</outputs>
<workflow name="test" version="1.0.0" engine="oozie" path="/user/guest/workflow" lib="/user/guest/workflowlib"/>
<retry policy="periodic" delay="hours(10)" attempts="3"/>
<late-process policy="exp-backoff" delay="hours(1)">
<late-input input="click" workflow-path="hdfs://clicks/late/workflow"/>
</late-process>
</process>
Where should the
process run?
How should the process
run?
What to consume?
What to produce?
Late Data Handling
Retry

22. Architecture
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25. Falcon Unit
A pipeline validation framework
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26. Motivation for Falcon Unit
● User errors caught only at deploy time.
● Input/Output feeds and paths not getting resolved.
● Errors in specification.
● Integration Tests require environment setup/tearDown.
● Messy deployment scripts.
● Debugging was cumbersome.
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27. Falcon Unit
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Falcon
Unit
In Process execution env.
● Local Oozie
● Local File System
● Local Job Runner
● Local Message Queue
Actual cluster
● Oozie
● HDFS
● YARN
● Active MQ
Test
suite

28. Example
Process Submission:
submit(EntityType.Process, <Path to Daily clicks Agg XML>); → Local
submit(EntityType.Process, <Path to Daily clicks Agg XML>); → Cluster Mode
Process Scheduling:
scheduleProcess(“daily_clicks_agg”, startTime, numInstances, clusterName);
Process Verification:
getInstanceStatus(EntityType.Process,“daily_clicks_agg”, scheduleTime);
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33. Deployment
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Embedded Mode

35. Distributed Mode
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36. Monitoring
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37. SLA Monitoring
●Alerts based on data Availability
●Dashboard
●Pluggable Alerting System
● Email
● JMS Notifications
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38. Pipeline view
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39. Triage
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41. ●Better Authentication and Authorization
●Even Better UI
●Even Better monitoring
●Process SLAs
●Streaming support
●A more powerful scheduler
●Pipeline Recovery
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42. Community
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44. Questions?
●Apache Falcon
● falcon.apache.org
● dev@falcon.apache.org / user@falcon.apache.org
●Ajay Yadava
● ajayyadava@apache.org
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