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1 © Hortonworks Inc. 2011 – 2017 All Rights Reserved
Protecting Your Critical Hadoop Clusters Against Disasters
DataWorks Summit – SydneySeptember 2017
2 © Hortonworks Inc. 2011 – 2017 All Rights Reserved
Presenters
Jeff Sposetti
Senior Director of Product Management, Hortonworks
Sankar Hariappan
Senior Software Engineer, Hortonworks
3 © Hortonworks Inc. 2011 – 2017 All Rights Reserved
Agenda
Background
Under the Hood / Deep Dive
Demonstration
Wrap Up
Q & A
4 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Background on DR + Backup
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What Is Disaster Recovery and Backup & Restore?
Disaster Recovery / Replication– Replication is copying data from Production Site to
Disaster Recovery Site
– Disaster Recovery includes replication, but also incorporates failover to Disaster Recovery site in case of outage and failback to the original Production Site
– Disaster Recovery Site can be an on-premise or cloud cluster
Backup & Restore– While Replication/Disaster Recovery protects against
disasters, it is can transport the logical errors (e.g. accidental deletion or corruption of data) to the DR Site
– To protect against accident deletion of your important HDFS directories or HBase Databases, customers need to do incremental/full backup (generally retained for 30 days) in order to restore back to a previous Point in time version
Production Site Disaster Recovery Site
Offsite Replication
Failback
Replication/Disaster Recovery
Sunday Monday Tuesday Wednesday Thursday Friday Saturday Sunday
Full Backup
Cumulative incremental backup Accidental Deletion
Backup & Restore
6 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Why Enterprise Customers Care?
Disaster Recovery (DR)– To maintain the business continuity, customers want replication, failover & failback capabilities across site. It
also becomes a compliance requirement
– Early adopter verticals are financials, Insurance, Healthcare, Payment Processing, Telco etc
Backup & Restore of business critical data– Customer want to backup and restore critical HDFS files, Hive Data, HBase Databases
Replication to Cloud– Customers want to move HDFS files/Hive external tables to S3/WASB/ADLS and spin up a compute cluster
– This enables a hybrid cloud deployment for our Enterprise customers
Hadoop Data Lake is becoming an integral part of Information Architecture in support of a data driven organization and many business critical applications are hosted on Hadoop infrastructure.
The High Availability of the business critical data across sites or Backup & Restore is critical
7 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Use Case Flow: Disaster Recovery of Hive/HDFS
Aactive
ARead only
Bactive
BRead only
Ce
ntr
aliz
ed
Se
curi
ty a
nd
Go
vern
ance
On-Premise
Data Center (a)
On-Premise
Data Center (b)
Scheduled Policy (A)
(2am, 10am, 6pm daily)
Scheduled Policy (B)
(2am daily)
Bactive
B’active
B’active
B’Read Only
ARead Only
1 Data replication with scheduled policy
2 Disaster takes down Data Center (b)
3 Failover to Data Center (a); data set B made active
4 Active data set B changes to B’ in Data Center (a)
5 Data center (b) is back up
6Failback to Data Center (b); B’ made passive in Data Center (a) and get re-synced to Data Center (b)
8 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Use Case Flow: Replication to Cloud Storage
Aactive
Apassive Public Cloud (C)
B’active
B’passive
b
Ce
ntr
aliz
ed
Se
curi
ty a
nd
Go
vern
ance
b
On-Premise
Data Center (a)
On-Premise
Data Center (b)
Manually Triggered
7 Trigger replication between Cloud and on-premcluster (scheduled or manual)
Use Case:
-Move Hive tables/partitions to cloud over-time for cloud native analytics
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Ideal Solution
Schedule and manage the replication policies
Subsystems supported: HDFS, Hive
Extensible to HBase & Kafka
HDFS Replication– Based on snapshots
– Restoration of to a prior snapshot state if there are errors during replication
– Automatic management of snapshots
Hive Replication– Support incremental replication of Hive
tables
– Replication policy can be created for each database in Hive warehouse
– Minimizes HDFS copies and provides a more consistent snapshot of state of source warehouse
Orchestration… Built on the Core Capabilities…
10 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Under the Hood / Deep Dive:Hive Replication
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Hive Replication: Design Goals
Metadata + Data replication
Point in time consistent replication
Efficient replication – transfer exact changes
Use cases– Disaster recovery
– Offload data processing to other clusters (perhaps in cloud)
Master – Slave replication (predictable)
12 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Event logging
HiveServer2 Hive Metastore
MetastoreRDBMS
Events table
JDBC/ODBC
Runs Query Retrieve/Store metadata
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Replicated Objects
Database
Table
Partition
Function
View
Constraint
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Event Based Replication
MetastoreRDBMS
Events TableHDFS
Serialize new events batch
Master Cluster
Slave Cluster
HiveServer2
Dump
(metadata + data)
HDFSMeatastore
RDBMSHiveServer2
DistcpMetastore API to write objects
Data files copy
Read repldump dir
REPL DUMP
REPL LOAD
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REPL Commands
"repl dump <db name> from <event id>" – get events newer than <event id>.
– Includes data files information.
– "<event id>" is last replicated event id for db from the destination cluster
"repl load <db name> from <hdfs URI>" – apply the events on destination
16 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Demonstration
17 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Wrap Up
18 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Takeaways
A Data Lake is becoming an integral part of Information Architecture in support of a data driven organization and many business critical applications are hosted on Hadoop infrastructure.
The availability of the business critical data across sites is critical.
DR and Backup solutions are powered by the replication capabilities of Hive and HDFS.
19 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Learn More
Disaster recovery and cloud migration for your Apache Hive warehouse
Breakout SessionThursday, September 21 @ 11:00a
https://dataworkssummit.com/sydney-2017/sessions/disaster-recovery-and-cloud-migration-for-your-apache-hive-warehouse/
Apache Hive, Apache HBase and Apache Phoenix
Bird of a FeatherThursday, September 21 @ 6:00p
https://dataworkssummit.com/sydney-2017/birds-of-a-feather/apache-hive-apache-hbase-apache-phoenix/
20 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Thank You.Questions?