SlideShare a Scribd company logo
1 of 18
Operations
Jeremy Carroll
Operations Engineer
HBaseCon 2013
We help people discover things they love
and inspire them to do those things…
HBase in Production
Overview
• All running on Amazon Web Services
• 5 production clusters and growing
• Mix SSD and SATA clusters
• Billions of page views per month
With lots of patches
Designing for EC2
• CDH 4.2.x
• HDFS-3912
• HBase 0.94.7
• HBASE-8284
• One zone per cluster / no rack locality
• RegionServers - Ephemeral disk only
• Redundant clusters for availability
• HDFS-4721 • HDFS-3703 • HDFS-9503
• HBASE-8389• HBASE-8434 • HBASE-7878
Configuration
Cluster Setup
• Managed splitting w/pre split tables
• Bloom filters for pretty much everything
• Manual / Rolling major compactions
• Reverse DNS on EC2
• 3 ZooKeepers in quorum
• 1 NameNode / Sec-NameNode / Master
• 1 EBS volume for fsImage / 1 Elastic IP
• 10-50 nodes per cluster
Fact-driven “Fry” method using Puppet
Provisioning
• User-data passed in to drive config management
• Repackaged modifications to HDFS / HBase
• Ubuntu .deb packages created with FPM
• Synced to S3, nodes configured with s3-apt plugin
• Mount + format ephemerals on boot
• Ext4 / nodiratime / nodealloc / lazy_itable_init
---- HBASE MODULE ----
class { 'hbase':
cluster => 'feeds_e',
namenode => 'ec2-xxx-xxx-xxx-xxx.compute-1.amazonaws.com',
zookeeper_quorum => 'zk1,zk2,zk3',
hbase_site_opts => {
'hbase.replication' => true,
'hbase.snapshot.enabled' => true,
'hbase.snapshot.region.timeout' => '35000',
'replication.sink.client.ops.timeout' => '20000',
'replication.sink.client.retries.number' => '3',
'replication.source.size.capacity' => '4194304',
'replication.source.nb.capacity' => '100',
...
}
}
---- FACT BASED VARIABLES ----
$hbase_heap_size = $ec2_instance_type ? {
'hi1.4xlarge' => '24000',
'm2.2xlarge' => '24000',
'm2.xlarge' => '11480',
'm1.xlarge' => '11480',
'm1.large' => '6500',
...
}
Puppet Module
Designed for EC2
Service Monitoring
• Wounded (dying) vs Operational
• High value metrics first
• Overall health
• Alive / dead nodes
• Service up/down
• Fsck / Blocks / % Space
• Replication status
• Regions needing splits
• fsImage checkpoint
• Zookeeper quorum
• Synthetic transactions (get / put)
• Queues (flush / compaction / rpc)
• Latency (client / filesystem)
Designed for EC2
Service Monitoring
Instrumentation
Metrics
• OpenTSDB for high cardinality metrics
• Per region stats collection
• tCollector
• RegionServer HTTP JMX
• HBase REST
• GangliaContext for hadoop-metrics
OpenTSDB
Table RegionServer Region
Slicing and Dicing
Using R
Tables
Regions
StoreFiles
Tuning Performance
Compaction
+Logs
Operational Intelligence
Dashboards
S3 + HBase Snapshots
Backups
• Full NameNode backup every 60 mins
• EBS Volume as an name.dir for crash recovery
• HBase snapshots + ExportSnapShot
Additional Tuning
Solid State Clusters
• Lower block size down from 32k
• Something a lot smaller. 8-16k
• Placement groups for 10Gb networking
• Increase DFSBandwidthPerSec
• Kernel tuning for TCP
• Compaction threads
• Disk elevator to noop
Process
Planning for Launch
• Pyres queue asynchronous reads / writes
• Allows for tuning a system before it goes live
• Tuning
• Schema
• Hot spots
• Compaction
• Canary roll out to new users
• 10% -> 30% -> 80% -> 100%
Pssstt. We’re hiring

More Related Content

What's hot

HBaseCon 2012 | Building a Large Search Platform on a Shoestring Budget
HBaseCon 2012 | Building a Large Search Platform on a Shoestring BudgetHBaseCon 2012 | Building a Large Search Platform on a Shoestring Budget
HBaseCon 2012 | Building a Large Search Platform on a Shoestring BudgetCloudera, Inc.
 
HBaseCon 2015 General Session: Zen - A Graph Data Model on HBase
HBaseCon 2015 General Session: Zen - A Graph Data Model on HBaseHBaseCon 2015 General Session: Zen - A Graph Data Model on HBase
HBaseCon 2015 General Session: Zen - A Graph Data Model on HBaseHBaseCon
 
HBaseCon 2013: Streaming Data into Apache HBase using Apache Flume: Experienc...
HBaseCon 2013: Streaming Data into Apache HBase using Apache Flume: Experienc...HBaseCon 2013: Streaming Data into Apache HBase using Apache Flume: Experienc...
HBaseCon 2013: Streaming Data into Apache HBase using Apache Flume: Experienc...Cloudera, Inc.
 
HBase at Bloomberg: High Availability Needs for the Financial Industry
HBase at Bloomberg: High Availability Needs for the Financial IndustryHBase at Bloomberg: High Availability Needs for the Financial Industry
HBase at Bloomberg: High Availability Needs for the Financial IndustryHBaseCon
 
HBaseCon 2013: Project Valta - A Resource Management Layer over Apache HBase
HBaseCon 2013: Project Valta - A Resource Management Layer over Apache HBaseHBaseCon 2013: Project Valta - A Resource Management Layer over Apache HBase
HBaseCon 2013: Project Valta - A Resource Management Layer over Apache HBaseCloudera, Inc.
 
HBaseCon 2012 | HBase Coprocessors – Deploy Shared Functionality Directly on ...
HBaseCon 2012 | HBase Coprocessors – Deploy Shared Functionality Directly on ...HBaseCon 2012 | HBase Coprocessors – Deploy Shared Functionality Directly on ...
HBaseCon 2012 | HBase Coprocessors – Deploy Shared Functionality Directly on ...Cloudera, Inc.
 
Optimizing Apache HBase for Cloud Storage in Microsoft Azure HDInsight
Optimizing Apache HBase for Cloud Storage in Microsoft Azure HDInsightOptimizing Apache HBase for Cloud Storage in Microsoft Azure HDInsight
Optimizing Apache HBase for Cloud Storage in Microsoft Azure HDInsightHBaseCon
 
HBaseCon 2012 | HBase and HDFS: Past, Present, Future - Todd Lipcon, Cloudera
HBaseCon 2012 | HBase and HDFS: Past, Present, Future - Todd Lipcon, ClouderaHBaseCon 2012 | HBase and HDFS: Past, Present, Future - Todd Lipcon, Cloudera
HBaseCon 2012 | HBase and HDFS: Past, Present, Future - Todd Lipcon, ClouderaCloudera, Inc.
 
Elastic HBase on Mesos - HBaseCon 2015
Elastic HBase on Mesos - HBaseCon 2015Elastic HBase on Mesos - HBaseCon 2015
Elastic HBase on Mesos - HBaseCon 2015Cosmin Lehene
 
Apache HBase in the Enterprise Data Hub at Cerner
Apache HBase in the Enterprise Data Hub at CernerApache HBase in the Enterprise Data Hub at Cerner
Apache HBase in the Enterprise Data Hub at CernerHBaseCon
 
HBaseCon 2012 | Solbase - Kyungseog Oh, Photobucket
HBaseCon 2012 | Solbase - Kyungseog Oh, PhotobucketHBaseCon 2012 | Solbase - Kyungseog Oh, Photobucket
HBaseCon 2012 | Solbase - Kyungseog Oh, PhotobucketCloudera, Inc.
 
HBase Read High Availability Using Timeline-Consistent Region Replicas
HBase Read High Availability Using Timeline-Consistent Region ReplicasHBase Read High Availability Using Timeline-Consistent Region Replicas
HBase Read High Availability Using Timeline-Consistent Region ReplicasHBaseCon
 
HBaseCon 2015: HBase and Spark
HBaseCon 2015: HBase and SparkHBaseCon 2015: HBase and Spark
HBaseCon 2015: HBase and SparkHBaseCon
 
HBaseCon 2015: State of HBase Docs and How to Contribute
HBaseCon 2015: State of HBase Docs and How to ContributeHBaseCon 2015: State of HBase Docs and How to Contribute
HBaseCon 2015: State of HBase Docs and How to ContributeHBaseCon
 
HBaseCon 2015- HBase @ Flipboard
HBaseCon 2015- HBase @ FlipboardHBaseCon 2015- HBase @ Flipboard
HBaseCon 2015- HBase @ FlipboardMatthew Blair
 
HBase Tales From the Trenches - Short stories about most common HBase operati...
HBase Tales From the Trenches - Short stories about most common HBase operati...HBase Tales From the Trenches - Short stories about most common HBase operati...
HBase Tales From the Trenches - Short stories about most common HBase operati...DataWorks Summit
 
HBaseCon 2013:High-Throughput, Transactional Stream Processing on Apache HBase
HBaseCon 2013:High-Throughput, Transactional Stream Processing on Apache HBase HBaseCon 2013:High-Throughput, Transactional Stream Processing on Apache HBase
HBaseCon 2013:High-Throughput, Transactional Stream Processing on Apache HBase Cloudera, Inc.
 
HBaseCon 2015: Elastic HBase on Mesos
HBaseCon 2015: Elastic HBase on MesosHBaseCon 2015: Elastic HBase on Mesos
HBaseCon 2015: Elastic HBase on MesosHBaseCon
 
HBase: Extreme Makeover
HBase: Extreme MakeoverHBase: Extreme Makeover
HBase: Extreme MakeoverHBaseCon
 

What's hot (20)

HBaseCon 2012 | Building a Large Search Platform on a Shoestring Budget
HBaseCon 2012 | Building a Large Search Platform on a Shoestring BudgetHBaseCon 2012 | Building a Large Search Platform on a Shoestring Budget
HBaseCon 2012 | Building a Large Search Platform on a Shoestring Budget
 
NoSQL: Cassadra vs. HBase
NoSQL: Cassadra vs. HBaseNoSQL: Cassadra vs. HBase
NoSQL: Cassadra vs. HBase
 
HBaseCon 2015 General Session: Zen - A Graph Data Model on HBase
HBaseCon 2015 General Session: Zen - A Graph Data Model on HBaseHBaseCon 2015 General Session: Zen - A Graph Data Model on HBase
HBaseCon 2015 General Session: Zen - A Graph Data Model on HBase
 
HBaseCon 2013: Streaming Data into Apache HBase using Apache Flume: Experienc...
HBaseCon 2013: Streaming Data into Apache HBase using Apache Flume: Experienc...HBaseCon 2013: Streaming Data into Apache HBase using Apache Flume: Experienc...
HBaseCon 2013: Streaming Data into Apache HBase using Apache Flume: Experienc...
 
HBase at Bloomberg: High Availability Needs for the Financial Industry
HBase at Bloomberg: High Availability Needs for the Financial IndustryHBase at Bloomberg: High Availability Needs for the Financial Industry
HBase at Bloomberg: High Availability Needs for the Financial Industry
 
HBaseCon 2013: Project Valta - A Resource Management Layer over Apache HBase
HBaseCon 2013: Project Valta - A Resource Management Layer over Apache HBaseHBaseCon 2013: Project Valta - A Resource Management Layer over Apache HBase
HBaseCon 2013: Project Valta - A Resource Management Layer over Apache HBase
 
HBaseCon 2012 | HBase Coprocessors – Deploy Shared Functionality Directly on ...
HBaseCon 2012 | HBase Coprocessors – Deploy Shared Functionality Directly on ...HBaseCon 2012 | HBase Coprocessors – Deploy Shared Functionality Directly on ...
HBaseCon 2012 | HBase Coprocessors – Deploy Shared Functionality Directly on ...
 
Optimizing Apache HBase for Cloud Storage in Microsoft Azure HDInsight
Optimizing Apache HBase for Cloud Storage in Microsoft Azure HDInsightOptimizing Apache HBase for Cloud Storage in Microsoft Azure HDInsight
Optimizing Apache HBase for Cloud Storage in Microsoft Azure HDInsight
 
HBaseCon 2012 | HBase and HDFS: Past, Present, Future - Todd Lipcon, Cloudera
HBaseCon 2012 | HBase and HDFS: Past, Present, Future - Todd Lipcon, ClouderaHBaseCon 2012 | HBase and HDFS: Past, Present, Future - Todd Lipcon, Cloudera
HBaseCon 2012 | HBase and HDFS: Past, Present, Future - Todd Lipcon, Cloudera
 
Elastic HBase on Mesos - HBaseCon 2015
Elastic HBase on Mesos - HBaseCon 2015Elastic HBase on Mesos - HBaseCon 2015
Elastic HBase on Mesos - HBaseCon 2015
 
Apache HBase in the Enterprise Data Hub at Cerner
Apache HBase in the Enterprise Data Hub at CernerApache HBase in the Enterprise Data Hub at Cerner
Apache HBase in the Enterprise Data Hub at Cerner
 
HBaseCon 2012 | Solbase - Kyungseog Oh, Photobucket
HBaseCon 2012 | Solbase - Kyungseog Oh, PhotobucketHBaseCon 2012 | Solbase - Kyungseog Oh, Photobucket
HBaseCon 2012 | Solbase - Kyungseog Oh, Photobucket
 
HBase Read High Availability Using Timeline-Consistent Region Replicas
HBase Read High Availability Using Timeline-Consistent Region ReplicasHBase Read High Availability Using Timeline-Consistent Region Replicas
HBase Read High Availability Using Timeline-Consistent Region Replicas
 
HBaseCon 2015: HBase and Spark
HBaseCon 2015: HBase and SparkHBaseCon 2015: HBase and Spark
HBaseCon 2015: HBase and Spark
 
HBaseCon 2015: State of HBase Docs and How to Contribute
HBaseCon 2015: State of HBase Docs and How to ContributeHBaseCon 2015: State of HBase Docs and How to Contribute
HBaseCon 2015: State of HBase Docs and How to Contribute
 
HBaseCon 2015- HBase @ Flipboard
HBaseCon 2015- HBase @ FlipboardHBaseCon 2015- HBase @ Flipboard
HBaseCon 2015- HBase @ Flipboard
 
HBase Tales From the Trenches - Short stories about most common HBase operati...
HBase Tales From the Trenches - Short stories about most common HBase operati...HBase Tales From the Trenches - Short stories about most common HBase operati...
HBase Tales From the Trenches - Short stories about most common HBase operati...
 
HBaseCon 2013:High-Throughput, Transactional Stream Processing on Apache HBase
HBaseCon 2013:High-Throughput, Transactional Stream Processing on Apache HBase HBaseCon 2013:High-Throughput, Transactional Stream Processing on Apache HBase
HBaseCon 2013:High-Throughput, Transactional Stream Processing on Apache HBase
 
HBaseCon 2015: Elastic HBase on Mesos
HBaseCon 2015: Elastic HBase on MesosHBaseCon 2015: Elastic HBase on Mesos
HBaseCon 2015: Elastic HBase on Mesos
 
HBase: Extreme Makeover
HBase: Extreme MakeoverHBase: Extreme Makeover
HBase: Extreme Makeover
 

Viewers also liked

HBaseCon 2012 | You’ve got HBase! How AOL Mail Handles Big Data
HBaseCon 2012 | You’ve got HBase! How AOL Mail Handles Big DataHBaseCon 2012 | You’ve got HBase! How AOL Mail Handles Big Data
HBaseCon 2012 | You’ve got HBase! How AOL Mail Handles Big DataCloudera, Inc.
 
HBaseCon 2015: Meet HBase 1.0
HBaseCon 2015: Meet HBase 1.0HBaseCon 2015: Meet HBase 1.0
HBaseCon 2015: Meet HBase 1.0HBaseCon
 
HBaseCon 2013: Apache HBase Table Snapshots
HBaseCon 2013: Apache HBase Table SnapshotsHBaseCon 2013: Apache HBase Table Snapshots
HBaseCon 2013: Apache HBase Table SnapshotsCloudera, Inc.
 
HBaseCon 2013: How to Get the MTTR Below 1 Minute and More
HBaseCon 2013: How to Get the MTTR Below 1 Minute and MoreHBaseCon 2013: How to Get the MTTR Below 1 Minute and More
HBaseCon 2013: How to Get the MTTR Below 1 Minute and MoreCloudera, Inc.
 
HBaseCon 2012 | Scaling GIS In Three Acts
HBaseCon 2012 | Scaling GIS In Three ActsHBaseCon 2012 | Scaling GIS In Three Acts
HBaseCon 2012 | Scaling GIS In Three ActsCloudera, Inc.
 
HBaseCon 2012 | HBase for the Worlds Libraries - OCLC
HBaseCon 2012 | HBase for the Worlds Libraries - OCLCHBaseCon 2012 | HBase for the Worlds Libraries - OCLC
HBaseCon 2012 | HBase for the Worlds Libraries - OCLCCloudera, Inc.
 
HBaseCon 2012 | Living Data: Applying Adaptable Schemas to HBase - Aaron Kimb...
HBaseCon 2012 | Living Data: Applying Adaptable Schemas to HBase - Aaron Kimb...HBaseCon 2012 | Living Data: Applying Adaptable Schemas to HBase - Aaron Kimb...
HBaseCon 2012 | Living Data: Applying Adaptable Schemas to HBase - Aaron Kimb...Cloudera, Inc.
 
HBaseCon 2013: Apache HBase, Meet Ops. Ops, Meet Apache HBase.
HBaseCon 2013: Apache HBase, Meet Ops. Ops, Meet Apache HBase.HBaseCon 2013: Apache HBase, Meet Ops. Ops, Meet Apache HBase.
HBaseCon 2013: Apache HBase, Meet Ops. Ops, Meet Apache HBase.Cloudera, Inc.
 
HBaseCon 2015: Trafodion - Integrating Operational SQL into HBase
HBaseCon 2015: Trafodion - Integrating Operational SQL into HBaseHBaseCon 2015: Trafodion - Integrating Operational SQL into HBase
HBaseCon 2015: Trafodion - Integrating Operational SQL into HBaseHBaseCon
 
HBaseCon 2013: Apache HBase on Flash
HBaseCon 2013: Apache HBase on FlashHBaseCon 2013: Apache HBase on Flash
HBaseCon 2013: Apache HBase on FlashCloudera, Inc.
 
HBaseCon 2013: 1500 JIRAs in 20 Minutes
HBaseCon 2013: 1500 JIRAs in 20 MinutesHBaseCon 2013: 1500 JIRAs in 20 Minutes
HBaseCon 2013: 1500 JIRAs in 20 MinutesCloudera, Inc.
 
HBaseCon 2012 | Leveraging HBase for the World’s Largest Curated Genomic Data...
HBaseCon 2012 | Leveraging HBase for the World’s Largest Curated Genomic Data...HBaseCon 2012 | Leveraging HBase for the World’s Largest Curated Genomic Data...
HBaseCon 2012 | Leveraging HBase for the World’s Largest Curated Genomic Data...Cloudera, Inc.
 
HBaseCon 2012 | Relaxed Transactions for HBase - Francis Liu, Yahoo!
HBaseCon 2012 | Relaxed Transactions for HBase - Francis Liu, Yahoo!HBaseCon 2012 | Relaxed Transactions for HBase - Francis Liu, Yahoo!
HBaseCon 2012 | Relaxed Transactions for HBase - Francis Liu, Yahoo!Cloudera, Inc.
 
HBaseCon 2012 | Building Mobile Infrastructure with HBase
HBaseCon 2012 | Building Mobile Infrastructure with HBaseHBaseCon 2012 | Building Mobile Infrastructure with HBase
HBaseCon 2012 | Building Mobile Infrastructure with HBaseCloudera, Inc.
 
Cross-Site BigTable using HBase
Cross-Site BigTable using HBaseCross-Site BigTable using HBase
Cross-Site BigTable using HBaseHBaseCon
 
HBaseCon 2015: DeathStar - Easy, Dynamic, Multi-tenant HBase via YARN
HBaseCon 2015: DeathStar - Easy, Dynamic,  Multi-tenant HBase via YARNHBaseCon 2015: DeathStar - Easy, Dynamic,  Multi-tenant HBase via YARN
HBaseCon 2015: DeathStar - Easy, Dynamic, Multi-tenant HBase via YARNHBaseCon
 
HBaseCon 2013: Apache Hadoop and Apache HBase for Real-Time Video Analytics
HBaseCon 2013: Apache Hadoop and Apache HBase for Real-Time Video Analytics HBaseCon 2013: Apache Hadoop and Apache HBase for Real-Time Video Analytics
HBaseCon 2013: Apache Hadoop and Apache HBase for Real-Time Video Analytics Cloudera, Inc.
 
HBaseCon 2012 | Content Addressable Storages for Fun and Profit - Berk Demir,...
HBaseCon 2012 | Content Addressable Storages for Fun and Profit - Berk Demir,...HBaseCon 2012 | Content Addressable Storages for Fun and Profit - Berk Demir,...
HBaseCon 2012 | Content Addressable Storages for Fun and Profit - Berk Demir,...Cloudera, Inc.
 
HBaseCon 2013: Evolving a First-Generation Apache HBase Deployment to Second...
HBaseCon 2013:  Evolving a First-Generation Apache HBase Deployment to Second...HBaseCon 2013:  Evolving a First-Generation Apache HBase Deployment to Second...
HBaseCon 2013: Evolving a First-Generation Apache HBase Deployment to Second...Cloudera, Inc.
 
HBaseCon 2012 | Unique Sets on HBase and Hadoop - Elliot Clark, StumbleUpon
HBaseCon 2012 | Unique Sets on HBase and Hadoop - Elliot Clark, StumbleUponHBaseCon 2012 | Unique Sets on HBase and Hadoop - Elliot Clark, StumbleUpon
HBaseCon 2012 | Unique Sets on HBase and Hadoop - Elliot Clark, StumbleUponCloudera, Inc.
 

Viewers also liked (20)

HBaseCon 2012 | You’ve got HBase! How AOL Mail Handles Big Data
HBaseCon 2012 | You’ve got HBase! How AOL Mail Handles Big DataHBaseCon 2012 | You’ve got HBase! How AOL Mail Handles Big Data
HBaseCon 2012 | You’ve got HBase! How AOL Mail Handles Big Data
 
HBaseCon 2015: Meet HBase 1.0
HBaseCon 2015: Meet HBase 1.0HBaseCon 2015: Meet HBase 1.0
HBaseCon 2015: Meet HBase 1.0
 
HBaseCon 2013: Apache HBase Table Snapshots
HBaseCon 2013: Apache HBase Table SnapshotsHBaseCon 2013: Apache HBase Table Snapshots
HBaseCon 2013: Apache HBase Table Snapshots
 
HBaseCon 2013: How to Get the MTTR Below 1 Minute and More
HBaseCon 2013: How to Get the MTTR Below 1 Minute and MoreHBaseCon 2013: How to Get the MTTR Below 1 Minute and More
HBaseCon 2013: How to Get the MTTR Below 1 Minute and More
 
HBaseCon 2012 | Scaling GIS In Three Acts
HBaseCon 2012 | Scaling GIS In Three ActsHBaseCon 2012 | Scaling GIS In Three Acts
HBaseCon 2012 | Scaling GIS In Three Acts
 
HBaseCon 2012 | HBase for the Worlds Libraries - OCLC
HBaseCon 2012 | HBase for the Worlds Libraries - OCLCHBaseCon 2012 | HBase for the Worlds Libraries - OCLC
HBaseCon 2012 | HBase for the Worlds Libraries - OCLC
 
HBaseCon 2012 | Living Data: Applying Adaptable Schemas to HBase - Aaron Kimb...
HBaseCon 2012 | Living Data: Applying Adaptable Schemas to HBase - Aaron Kimb...HBaseCon 2012 | Living Data: Applying Adaptable Schemas to HBase - Aaron Kimb...
HBaseCon 2012 | Living Data: Applying Adaptable Schemas to HBase - Aaron Kimb...
 
HBaseCon 2013: Apache HBase, Meet Ops. Ops, Meet Apache HBase.
HBaseCon 2013: Apache HBase, Meet Ops. Ops, Meet Apache HBase.HBaseCon 2013: Apache HBase, Meet Ops. Ops, Meet Apache HBase.
HBaseCon 2013: Apache HBase, Meet Ops. Ops, Meet Apache HBase.
 
HBaseCon 2015: Trafodion - Integrating Operational SQL into HBase
HBaseCon 2015: Trafodion - Integrating Operational SQL into HBaseHBaseCon 2015: Trafodion - Integrating Operational SQL into HBase
HBaseCon 2015: Trafodion - Integrating Operational SQL into HBase
 
HBaseCon 2013: Apache HBase on Flash
HBaseCon 2013: Apache HBase on FlashHBaseCon 2013: Apache HBase on Flash
HBaseCon 2013: Apache HBase on Flash
 
HBaseCon 2013: 1500 JIRAs in 20 Minutes
HBaseCon 2013: 1500 JIRAs in 20 MinutesHBaseCon 2013: 1500 JIRAs in 20 Minutes
HBaseCon 2013: 1500 JIRAs in 20 Minutes
 
HBaseCon 2012 | Leveraging HBase for the World’s Largest Curated Genomic Data...
HBaseCon 2012 | Leveraging HBase for the World’s Largest Curated Genomic Data...HBaseCon 2012 | Leveraging HBase for the World’s Largest Curated Genomic Data...
HBaseCon 2012 | Leveraging HBase for the World’s Largest Curated Genomic Data...
 
HBaseCon 2012 | Relaxed Transactions for HBase - Francis Liu, Yahoo!
HBaseCon 2012 | Relaxed Transactions for HBase - Francis Liu, Yahoo!HBaseCon 2012 | Relaxed Transactions for HBase - Francis Liu, Yahoo!
HBaseCon 2012 | Relaxed Transactions for HBase - Francis Liu, Yahoo!
 
HBaseCon 2012 | Building Mobile Infrastructure with HBase
HBaseCon 2012 | Building Mobile Infrastructure with HBaseHBaseCon 2012 | Building Mobile Infrastructure with HBase
HBaseCon 2012 | Building Mobile Infrastructure with HBase
 
Cross-Site BigTable using HBase
Cross-Site BigTable using HBaseCross-Site BigTable using HBase
Cross-Site BigTable using HBase
 
HBaseCon 2015: DeathStar - Easy, Dynamic, Multi-tenant HBase via YARN
HBaseCon 2015: DeathStar - Easy, Dynamic,  Multi-tenant HBase via YARNHBaseCon 2015: DeathStar - Easy, Dynamic,  Multi-tenant HBase via YARN
HBaseCon 2015: DeathStar - Easy, Dynamic, Multi-tenant HBase via YARN
 
HBaseCon 2013: Apache Hadoop and Apache HBase for Real-Time Video Analytics
HBaseCon 2013: Apache Hadoop and Apache HBase for Real-Time Video Analytics HBaseCon 2013: Apache Hadoop and Apache HBase for Real-Time Video Analytics
HBaseCon 2013: Apache Hadoop and Apache HBase for Real-Time Video Analytics
 
HBaseCon 2012 | Content Addressable Storages for Fun and Profit - Berk Demir,...
HBaseCon 2012 | Content Addressable Storages for Fun and Profit - Berk Demir,...HBaseCon 2012 | Content Addressable Storages for Fun and Profit - Berk Demir,...
HBaseCon 2012 | Content Addressable Storages for Fun and Profit - Berk Demir,...
 
HBaseCon 2013: Evolving a First-Generation Apache HBase Deployment to Second...
HBaseCon 2013:  Evolving a First-Generation Apache HBase Deployment to Second...HBaseCon 2013:  Evolving a First-Generation Apache HBase Deployment to Second...
HBaseCon 2013: Evolving a First-Generation Apache HBase Deployment to Second...
 
HBaseCon 2012 | Unique Sets on HBase and Hadoop - Elliot Clark, StumbleUpon
HBaseCon 2012 | Unique Sets on HBase and Hadoop - Elliot Clark, StumbleUponHBaseCon 2012 | Unique Sets on HBase and Hadoop - Elliot Clark, StumbleUpon
HBaseCon 2012 | Unique Sets on HBase and Hadoop - Elliot Clark, StumbleUpon
 

Similar to HBaseCon 2013: Apache HBase Operations at Pinterest

Slides for the Apache Geode Hands-on Meetup and Hackathon Announcement
Slides for the Apache Geode Hands-on Meetup and Hackathon Announcement Slides for the Apache Geode Hands-on Meetup and Hackathon Announcement
Slides for the Apache Geode Hands-on Meetup and Hackathon Announcement VMware Tanzu
 
Orchestrating Docker with Terraform and Consul by Mitchell Hashimoto
Orchestrating Docker with Terraform and Consul by Mitchell Hashimoto Orchestrating Docker with Terraform and Consul by Mitchell Hashimoto
Orchestrating Docker with Terraform and Consul by Mitchell Hashimoto Docker, Inc.
 
How does Apache Pegasus (incubating) community develop at SensorsData
How does Apache Pegasus (incubating) community develop at SensorsDataHow does Apache Pegasus (incubating) community develop at SensorsData
How does Apache Pegasus (incubating) community develop at SensorsDataacelyc1112009
 
C* Summit 2013: Cassandra at eBay Scale by Feng Qu and Anurag Jambhekar
C* Summit 2013: Cassandra at eBay Scale by Feng Qu and Anurag JambhekarC* Summit 2013: Cassandra at eBay Scale by Feng Qu and Anurag Jambhekar
C* Summit 2013: Cassandra at eBay Scale by Feng Qu and Anurag JambhekarDataStax Academy
 
AWS Database Services-Philadelphia AWS User Group-4-17-2018
AWS Database Services-Philadelphia AWS User Group-4-17-2018AWS Database Services-Philadelphia AWS User Group-4-17-2018
AWS Database Services-Philadelphia AWS User Group-4-17-2018Bert Zahniser
 
ECS19 - Patrick Curran, Eric Shupps - SHAREPOINT 24X7X365: ARCHITECTING FOR H...
ECS19 - Patrick Curran, Eric Shupps - SHAREPOINT 24X7X365: ARCHITECTING FOR H...ECS19 - Patrick Curran, Eric Shupps - SHAREPOINT 24X7X365: ARCHITECTING FOR H...
ECS19 - Patrick Curran, Eric Shupps - SHAREPOINT 24X7X365: ARCHITECTING FOR H...European Collaboration Summit
 
HadoopCon2015 Multi-Cluster Live Synchronization with Kerberos Federated Hadoop
HadoopCon2015 Multi-Cluster Live Synchronization with Kerberos Federated HadoopHadoopCon2015 Multi-Cluster Live Synchronization with Kerberos Federated Hadoop
HadoopCon2015 Multi-Cluster Live Synchronization with Kerberos Federated HadoopYafang Chang
 
Performance Optimizations in Apache Impala
Performance Optimizations in Apache ImpalaPerformance Optimizations in Apache Impala
Performance Optimizations in Apache ImpalaCloudera, Inc.
 
BDA 302 Deep Dive on Migrating Big Data Workloads to Amazon EMR
BDA 302 Deep Dive on Migrating Big Data Workloads to Amazon EMRBDA 302 Deep Dive on Migrating Big Data Workloads to Amazon EMR
BDA 302 Deep Dive on Migrating Big Data Workloads to Amazon EMRAmazon Web Services
 
HBaseConAsia2018 Track3-2: HBase at China Telecom
HBaseConAsia2018 Track3-2:  HBase at China TelecomHBaseConAsia2018 Track3-2:  HBase at China Telecom
HBaseConAsia2018 Track3-2: HBase at China TelecomMichael Stack
 
Rigorous and Multi-tenant HBase Performance
Rigorous and Multi-tenant HBase PerformanceRigorous and Multi-tenant HBase Performance
Rigorous and Multi-tenant HBase PerformanceCloudera, Inc.
 
Kognitio - an overview
Kognitio - an overviewKognitio - an overview
Kognitio - an overviewKognitio
 
Open stack ha design & deployment kilo
Open stack ha design & deployment   kiloOpen stack ha design & deployment   kilo
Open stack ha design & deployment kiloSteven Li
 
Fast SQL on Hadoop, really?
Fast SQL on Hadoop, really?Fast SQL on Hadoop, really?
Fast SQL on Hadoop, really?DataWorks Summit
 
Real-time Big Data Analytics Engine using Impala
Real-time Big Data Analytics Engine using ImpalaReal-time Big Data Analytics Engine using Impala
Real-time Big Data Analytics Engine using ImpalaJason Shih
 
Tech-Spark: SQL Server on Linux
Tech-Spark: SQL Server on LinuxTech-Spark: SQL Server on Linux
Tech-Spark: SQL Server on LinuxRalph Attard
 
Tuning Apache Ambari performance for Big Data at scale with 3000 agents
Tuning Apache Ambari performance for Big Data at scale with 3000 agentsTuning Apache Ambari performance for Big Data at scale with 3000 agents
Tuning Apache Ambari performance for Big Data at scale with 3000 agentsDataWorks Summit
 

Similar to HBaseCon 2013: Apache HBase Operations at Pinterest (20)

Slides for the Apache Geode Hands-on Meetup and Hackathon Announcement
Slides for the Apache Geode Hands-on Meetup and Hackathon Announcement Slides for the Apache Geode Hands-on Meetup and Hackathon Announcement
Slides for the Apache Geode Hands-on Meetup and Hackathon Announcement
 
Orchestrating Docker with Terraform and Consul by Mitchell Hashimoto
Orchestrating Docker with Terraform and Consul by Mitchell Hashimoto Orchestrating Docker with Terraform and Consul by Mitchell Hashimoto
Orchestrating Docker with Terraform and Consul by Mitchell Hashimoto
 
Sum209
Sum209Sum209
Sum209
 
How does Apache Pegasus (incubating) community develop at SensorsData
How does Apache Pegasus (incubating) community develop at SensorsDataHow does Apache Pegasus (incubating) community develop at SensorsData
How does Apache Pegasus (incubating) community develop at SensorsData
 
C* Summit 2013: Cassandra at eBay Scale by Feng Qu and Anurag Jambhekar
C* Summit 2013: Cassandra at eBay Scale by Feng Qu and Anurag JambhekarC* Summit 2013: Cassandra at eBay Scale by Feng Qu and Anurag Jambhekar
C* Summit 2013: Cassandra at eBay Scale by Feng Qu and Anurag Jambhekar
 
AWS Database Services-Philadelphia AWS User Group-4-17-2018
AWS Database Services-Philadelphia AWS User Group-4-17-2018AWS Database Services-Philadelphia AWS User Group-4-17-2018
AWS Database Services-Philadelphia AWS User Group-4-17-2018
 
What's New in Apache Hive
What's New in Apache HiveWhat's New in Apache Hive
What's New in Apache Hive
 
ECS19 - Patrick Curran, Eric Shupps - SHAREPOINT 24X7X365: ARCHITECTING FOR H...
ECS19 - Patrick Curran, Eric Shupps - SHAREPOINT 24X7X365: ARCHITECTING FOR H...ECS19 - Patrick Curran, Eric Shupps - SHAREPOINT 24X7X365: ARCHITECTING FOR H...
ECS19 - Patrick Curran, Eric Shupps - SHAREPOINT 24X7X365: ARCHITECTING FOR H...
 
Redshift overview
Redshift overviewRedshift overview
Redshift overview
 
HadoopCon2015 Multi-Cluster Live Synchronization with Kerberos Federated Hadoop
HadoopCon2015 Multi-Cluster Live Synchronization with Kerberos Federated HadoopHadoopCon2015 Multi-Cluster Live Synchronization with Kerberos Federated Hadoop
HadoopCon2015 Multi-Cluster Live Synchronization with Kerberos Federated Hadoop
 
Performance Optimizations in Apache Impala
Performance Optimizations in Apache ImpalaPerformance Optimizations in Apache Impala
Performance Optimizations in Apache Impala
 
BDA 302 Deep Dive on Migrating Big Data Workloads to Amazon EMR
BDA 302 Deep Dive on Migrating Big Data Workloads to Amazon EMRBDA 302 Deep Dive on Migrating Big Data Workloads to Amazon EMR
BDA 302 Deep Dive on Migrating Big Data Workloads to Amazon EMR
 
HBaseConAsia2018 Track3-2: HBase at China Telecom
HBaseConAsia2018 Track3-2:  HBase at China TelecomHBaseConAsia2018 Track3-2:  HBase at China Telecom
HBaseConAsia2018 Track3-2: HBase at China Telecom
 
Rigorous and Multi-tenant HBase Performance
Rigorous and Multi-tenant HBase PerformanceRigorous and Multi-tenant HBase Performance
Rigorous and Multi-tenant HBase Performance
 
Kognitio - an overview
Kognitio - an overviewKognitio - an overview
Kognitio - an overview
 
Open stack ha design & deployment kilo
Open stack ha design & deployment   kiloOpen stack ha design & deployment   kilo
Open stack ha design & deployment kilo
 
Fast SQL on Hadoop, really?
Fast SQL on Hadoop, really?Fast SQL on Hadoop, really?
Fast SQL on Hadoop, really?
 
Real-time Big Data Analytics Engine using Impala
Real-time Big Data Analytics Engine using ImpalaReal-time Big Data Analytics Engine using Impala
Real-time Big Data Analytics Engine using Impala
 
Tech-Spark: SQL Server on Linux
Tech-Spark: SQL Server on LinuxTech-Spark: SQL Server on Linux
Tech-Spark: SQL Server on Linux
 
Tuning Apache Ambari performance for Big Data at scale with 3000 agents
Tuning Apache Ambari performance for Big Data at scale with 3000 agentsTuning Apache Ambari performance for Big Data at scale with 3000 agents
Tuning Apache Ambari performance for Big Data at scale with 3000 agents
 

More from Cloudera, Inc.

Partner Briefing_January 25 (FINAL).pptx
Partner Briefing_January 25 (FINAL).pptxPartner Briefing_January 25 (FINAL).pptx
Partner Briefing_January 25 (FINAL).pptxCloudera, Inc.
 
Cloudera Data Impact Awards 2021 - Finalists
Cloudera Data Impact Awards 2021 - Finalists Cloudera Data Impact Awards 2021 - Finalists
Cloudera Data Impact Awards 2021 - Finalists Cloudera, Inc.
 
2020 Cloudera Data Impact Awards Finalists
2020 Cloudera Data Impact Awards Finalists2020 Cloudera Data Impact Awards Finalists
2020 Cloudera Data Impact Awards FinalistsCloudera, Inc.
 
Edc event vienna presentation 1 oct 2019
Edc event vienna presentation 1 oct 2019Edc event vienna presentation 1 oct 2019
Edc event vienna presentation 1 oct 2019Cloudera, Inc.
 
Machine Learning with Limited Labeled Data 4/3/19
Machine Learning with Limited Labeled Data 4/3/19Machine Learning with Limited Labeled Data 4/3/19
Machine Learning with Limited Labeled Data 4/3/19Cloudera, Inc.
 
Data Driven With the Cloudera Modern Data Warehouse 3.19.19
Data Driven With the Cloudera Modern Data Warehouse 3.19.19Data Driven With the Cloudera Modern Data Warehouse 3.19.19
Data Driven With the Cloudera Modern Data Warehouse 3.19.19Cloudera, Inc.
 
Introducing Cloudera DataFlow (CDF) 2.13.19
Introducing Cloudera DataFlow (CDF) 2.13.19Introducing Cloudera DataFlow (CDF) 2.13.19
Introducing Cloudera DataFlow (CDF) 2.13.19Cloudera, Inc.
 
Introducing Cloudera Data Science Workbench for HDP 2.12.19
Introducing Cloudera Data Science Workbench for HDP 2.12.19Introducing Cloudera Data Science Workbench for HDP 2.12.19
Introducing Cloudera Data Science Workbench for HDP 2.12.19Cloudera, Inc.
 
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19Cloudera, Inc.
 
Leveraging the cloud for analytics and machine learning 1.29.19
Leveraging the cloud for analytics and machine learning 1.29.19Leveraging the cloud for analytics and machine learning 1.29.19
Leveraging the cloud for analytics and machine learning 1.29.19Cloudera, Inc.
 
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19Cloudera, Inc.
 
Leveraging the Cloud for Big Data Analytics 12.11.18
Leveraging the Cloud for Big Data Analytics 12.11.18Leveraging the Cloud for Big Data Analytics 12.11.18
Leveraging the Cloud for Big Data Analytics 12.11.18Cloudera, Inc.
 
Modern Data Warehouse Fundamentals Part 3
Modern Data Warehouse Fundamentals Part 3Modern Data Warehouse Fundamentals Part 3
Modern Data Warehouse Fundamentals Part 3Cloudera, Inc.
 
Modern Data Warehouse Fundamentals Part 2
Modern Data Warehouse Fundamentals Part 2Modern Data Warehouse Fundamentals Part 2
Modern Data Warehouse Fundamentals Part 2Cloudera, Inc.
 
Modern Data Warehouse Fundamentals Part 1
Modern Data Warehouse Fundamentals Part 1Modern Data Warehouse Fundamentals Part 1
Modern Data Warehouse Fundamentals Part 1Cloudera, Inc.
 
Extending Cloudera SDX beyond the Platform
Extending Cloudera SDX beyond the PlatformExtending Cloudera SDX beyond the Platform
Extending Cloudera SDX beyond the PlatformCloudera, Inc.
 
Federated Learning: ML with Privacy on the Edge 11.15.18
Federated Learning: ML with Privacy on the Edge 11.15.18Federated Learning: ML with Privacy on the Edge 11.15.18
Federated Learning: ML with Privacy on the Edge 11.15.18Cloudera, Inc.
 
Analyst Webinar: Doing a 180 on Customer 360
Analyst Webinar: Doing a 180 on Customer 360Analyst Webinar: Doing a 180 on Customer 360
Analyst Webinar: Doing a 180 on Customer 360Cloudera, Inc.
 
Build a modern platform for anti-money laundering 9.19.18
Build a modern platform for anti-money laundering 9.19.18Build a modern platform for anti-money laundering 9.19.18
Build a modern platform for anti-money laundering 9.19.18Cloudera, Inc.
 
Introducing the data science sandbox as a service 8.30.18
Introducing the data science sandbox as a service 8.30.18Introducing the data science sandbox as a service 8.30.18
Introducing the data science sandbox as a service 8.30.18Cloudera, Inc.
 

More from Cloudera, Inc. (20)

Partner Briefing_January 25 (FINAL).pptx
Partner Briefing_January 25 (FINAL).pptxPartner Briefing_January 25 (FINAL).pptx
Partner Briefing_January 25 (FINAL).pptx
 
Cloudera Data Impact Awards 2021 - Finalists
Cloudera Data Impact Awards 2021 - Finalists Cloudera Data Impact Awards 2021 - Finalists
Cloudera Data Impact Awards 2021 - Finalists
 
2020 Cloudera Data Impact Awards Finalists
2020 Cloudera Data Impact Awards Finalists2020 Cloudera Data Impact Awards Finalists
2020 Cloudera Data Impact Awards Finalists
 
Edc event vienna presentation 1 oct 2019
Edc event vienna presentation 1 oct 2019Edc event vienna presentation 1 oct 2019
Edc event vienna presentation 1 oct 2019
 
Machine Learning with Limited Labeled Data 4/3/19
Machine Learning with Limited Labeled Data 4/3/19Machine Learning with Limited Labeled Data 4/3/19
Machine Learning with Limited Labeled Data 4/3/19
 
Data Driven With the Cloudera Modern Data Warehouse 3.19.19
Data Driven With the Cloudera Modern Data Warehouse 3.19.19Data Driven With the Cloudera Modern Data Warehouse 3.19.19
Data Driven With the Cloudera Modern Data Warehouse 3.19.19
 
Introducing Cloudera DataFlow (CDF) 2.13.19
Introducing Cloudera DataFlow (CDF) 2.13.19Introducing Cloudera DataFlow (CDF) 2.13.19
Introducing Cloudera DataFlow (CDF) 2.13.19
 
Introducing Cloudera Data Science Workbench for HDP 2.12.19
Introducing Cloudera Data Science Workbench for HDP 2.12.19Introducing Cloudera Data Science Workbench for HDP 2.12.19
Introducing Cloudera Data Science Workbench for HDP 2.12.19
 
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19
 
Leveraging the cloud for analytics and machine learning 1.29.19
Leveraging the cloud for analytics and machine learning 1.29.19Leveraging the cloud for analytics and machine learning 1.29.19
Leveraging the cloud for analytics and machine learning 1.29.19
 
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19
 
Leveraging the Cloud for Big Data Analytics 12.11.18
Leveraging the Cloud for Big Data Analytics 12.11.18Leveraging the Cloud for Big Data Analytics 12.11.18
Leveraging the Cloud for Big Data Analytics 12.11.18
 
Modern Data Warehouse Fundamentals Part 3
Modern Data Warehouse Fundamentals Part 3Modern Data Warehouse Fundamentals Part 3
Modern Data Warehouse Fundamentals Part 3
 
Modern Data Warehouse Fundamentals Part 2
Modern Data Warehouse Fundamentals Part 2Modern Data Warehouse Fundamentals Part 2
Modern Data Warehouse Fundamentals Part 2
 
Modern Data Warehouse Fundamentals Part 1
Modern Data Warehouse Fundamentals Part 1Modern Data Warehouse Fundamentals Part 1
Modern Data Warehouse Fundamentals Part 1
 
Extending Cloudera SDX beyond the Platform
Extending Cloudera SDX beyond the PlatformExtending Cloudera SDX beyond the Platform
Extending Cloudera SDX beyond the Platform
 
Federated Learning: ML with Privacy on the Edge 11.15.18
Federated Learning: ML with Privacy on the Edge 11.15.18Federated Learning: ML with Privacy on the Edge 11.15.18
Federated Learning: ML with Privacy on the Edge 11.15.18
 
Analyst Webinar: Doing a 180 on Customer 360
Analyst Webinar: Doing a 180 on Customer 360Analyst Webinar: Doing a 180 on Customer 360
Analyst Webinar: Doing a 180 on Customer 360
 
Build a modern platform for anti-money laundering 9.19.18
Build a modern platform for anti-money laundering 9.19.18Build a modern platform for anti-money laundering 9.19.18
Build a modern platform for anti-money laundering 9.19.18
 
Introducing the data science sandbox as a service 8.30.18
Introducing the data science sandbox as a service 8.30.18Introducing the data science sandbox as a service 8.30.18
Introducing the data science sandbox as a service 8.30.18
 

Recently uploaded

3 Pitfalls Everyone Should Avoid with Cloud Data
3 Pitfalls Everyone Should Avoid with Cloud Data3 Pitfalls Everyone Should Avoid with Cloud Data
3 Pitfalls Everyone Should Avoid with Cloud DataEric D. Schabell
 
Automation Ops Series: Session 2 - Governance for UiPath projects
Automation Ops Series: Session 2 - Governance for UiPath projectsAutomation Ops Series: Session 2 - Governance for UiPath projects
Automation Ops Series: Session 2 - Governance for UiPath projectsDianaGray10
 
SIM INFORMATION SYSTEM: REVOLUTIONIZING DATA MANAGEMENT
SIM INFORMATION SYSTEM: REVOLUTIONIZING DATA MANAGEMENTSIM INFORMATION SYSTEM: REVOLUTIONIZING DATA MANAGEMENT
SIM INFORMATION SYSTEM: REVOLUTIONIZING DATA MANAGEMENTxtailishbaloch
 
Key Trends Shaping the Future of Infrastructure.pdf
Key Trends Shaping the Future of Infrastructure.pdfKey Trends Shaping the Future of Infrastructure.pdf
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
 
UiPath Studio Web workshop series - Day 4
UiPath Studio Web workshop series - Day 4UiPath Studio Web workshop series - Day 4
UiPath Studio Web workshop series - Day 4DianaGray10
 
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptxEmil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptxNeo4j
 
AI Workshops at Computers In Libraries 2024
AI Workshops at Computers In Libraries 2024AI Workshops at Computers In Libraries 2024
AI Workshops at Computers In Libraries 2024Brian Pichman
 
Technical SEO for Improved Accessibility WTS FEST
Technical SEO for Improved Accessibility  WTS FESTTechnical SEO for Improved Accessibility  WTS FEST
Technical SEO for Improved Accessibility WTS FESTBillieHyde
 
Scenario Library et REX Discover industry- and role- based scenarios
Scenario Library et REX Discover industry- and role- based scenariosScenario Library et REX Discover industry- and role- based scenarios
Scenario Library et REX Discover industry- and role- based scenariosErol GIRAUDY
 
March Patch Tuesday
March Patch TuesdayMarch Patch Tuesday
March Patch TuesdayIvanti
 
20140402 - Smart house demo kit
20140402 - Smart house demo kit20140402 - Smart house demo kit
20140402 - Smart house demo kitJamie (Taka) Wang
 
Q4 2023 Quarterly Investor Presentation - FINAL - v1.pdf
Q4 2023 Quarterly Investor Presentation - FINAL - v1.pdfQ4 2023 Quarterly Investor Presentation - FINAL - v1.pdf
Q4 2023 Quarterly Investor Presentation - FINAL - v1.pdfTejal81
 
Introduction - IPLOOK NETWORKS CO., LTD.
Introduction - IPLOOK NETWORKS CO., LTD.Introduction - IPLOOK NETWORKS CO., LTD.
Introduction - IPLOOK NETWORKS CO., LTD.IPLOOK Networks
 
The Zero-ETL Approach: Enhancing Data Agility and Insight
The Zero-ETL Approach: Enhancing Data Agility and InsightThe Zero-ETL Approach: Enhancing Data Agility and Insight
The Zero-ETL Approach: Enhancing Data Agility and InsightSafe Software
 
Graphene Quantum Dots-Based Composites for Biomedical Applications
Graphene Quantum Dots-Based Composites for  Biomedical ApplicationsGraphene Quantum Dots-Based Composites for  Biomedical Applications
Graphene Quantum Dots-Based Composites for Biomedical Applicationsnooralam814309
 
The New Cloud World Order Is FinOps (Slideshow)
The New Cloud World Order Is FinOps (Slideshow)The New Cloud World Order Is FinOps (Slideshow)
The New Cloud World Order Is FinOps (Slideshow)codyslingerland1
 
2024.03.12 Cost drivers of cultivated meat production.pdf
2024.03.12 Cost drivers of cultivated meat production.pdf2024.03.12 Cost drivers of cultivated meat production.pdf
2024.03.12 Cost drivers of cultivated meat production.pdfThe Good Food Institute
 
My key hands-on projects in Quantum, and QAI
My key hands-on projects in Quantum, and QAIMy key hands-on projects in Quantum, and QAI
My key hands-on projects in Quantum, and QAIVijayananda Mohire
 
Patch notes explaining DISARM Version 1.4 update
Patch notes explaining DISARM Version 1.4 updatePatch notes explaining DISARM Version 1.4 update
Patch notes explaining DISARM Version 1.4 updateadam112203
 

Recently uploaded (20)

3 Pitfalls Everyone Should Avoid with Cloud Data
3 Pitfalls Everyone Should Avoid with Cloud Data3 Pitfalls Everyone Should Avoid with Cloud Data
3 Pitfalls Everyone Should Avoid with Cloud Data
 
Automation Ops Series: Session 2 - Governance for UiPath projects
Automation Ops Series: Session 2 - Governance for UiPath projectsAutomation Ops Series: Session 2 - Governance for UiPath projects
Automation Ops Series: Session 2 - Governance for UiPath projects
 
SIM INFORMATION SYSTEM: REVOLUTIONIZING DATA MANAGEMENT
SIM INFORMATION SYSTEM: REVOLUTIONIZING DATA MANAGEMENTSIM INFORMATION SYSTEM: REVOLUTIONIZING DATA MANAGEMENT
SIM INFORMATION SYSTEM: REVOLUTIONIZING DATA MANAGEMENT
 
Key Trends Shaping the Future of Infrastructure.pdf
Key Trends Shaping the Future of Infrastructure.pdfKey Trends Shaping the Future of Infrastructure.pdf
Key Trends Shaping the Future of Infrastructure.pdf
 
UiPath Studio Web workshop series - Day 4
UiPath Studio Web workshop series - Day 4UiPath Studio Web workshop series - Day 4
UiPath Studio Web workshop series - Day 4
 
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptxEmil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
 
AI Workshops at Computers In Libraries 2024
AI Workshops at Computers In Libraries 2024AI Workshops at Computers In Libraries 2024
AI Workshops at Computers In Libraries 2024
 
Technical SEO for Improved Accessibility WTS FEST
Technical SEO for Improved Accessibility  WTS FESTTechnical SEO for Improved Accessibility  WTS FEST
Technical SEO for Improved Accessibility WTS FEST
 
Scenario Library et REX Discover industry- and role- based scenarios
Scenario Library et REX Discover industry- and role- based scenariosScenario Library et REX Discover industry- and role- based scenarios
Scenario Library et REX Discover industry- and role- based scenarios
 
March Patch Tuesday
March Patch TuesdayMarch Patch Tuesday
March Patch Tuesday
 
20140402 - Smart house demo kit
20140402 - Smart house demo kit20140402 - Smart house demo kit
20140402 - Smart house demo kit
 
Q4 2023 Quarterly Investor Presentation - FINAL - v1.pdf
Q4 2023 Quarterly Investor Presentation - FINAL - v1.pdfQ4 2023 Quarterly Investor Presentation - FINAL - v1.pdf
Q4 2023 Quarterly Investor Presentation - FINAL - v1.pdf
 
SheDev 2024
SheDev 2024SheDev 2024
SheDev 2024
 
Introduction - IPLOOK NETWORKS CO., LTD.
Introduction - IPLOOK NETWORKS CO., LTD.Introduction - IPLOOK NETWORKS CO., LTD.
Introduction - IPLOOK NETWORKS CO., LTD.
 
The Zero-ETL Approach: Enhancing Data Agility and Insight
The Zero-ETL Approach: Enhancing Data Agility and InsightThe Zero-ETL Approach: Enhancing Data Agility and Insight
The Zero-ETL Approach: Enhancing Data Agility and Insight
 
Graphene Quantum Dots-Based Composites for Biomedical Applications
Graphene Quantum Dots-Based Composites for  Biomedical ApplicationsGraphene Quantum Dots-Based Composites for  Biomedical Applications
Graphene Quantum Dots-Based Composites for Biomedical Applications
 
The New Cloud World Order Is FinOps (Slideshow)
The New Cloud World Order Is FinOps (Slideshow)The New Cloud World Order Is FinOps (Slideshow)
The New Cloud World Order Is FinOps (Slideshow)
 
2024.03.12 Cost drivers of cultivated meat production.pdf
2024.03.12 Cost drivers of cultivated meat production.pdf2024.03.12 Cost drivers of cultivated meat production.pdf
2024.03.12 Cost drivers of cultivated meat production.pdf
 
My key hands-on projects in Quantum, and QAI
My key hands-on projects in Quantum, and QAIMy key hands-on projects in Quantum, and QAI
My key hands-on projects in Quantum, and QAI
 
Patch notes explaining DISARM Version 1.4 update
Patch notes explaining DISARM Version 1.4 updatePatch notes explaining DISARM Version 1.4 update
Patch notes explaining DISARM Version 1.4 update
 

HBaseCon 2013: Apache HBase Operations at Pinterest

  • 2. We help people discover things they love and inspire them to do those things…
  • 3. HBase in Production Overview • All running on Amazon Web Services • 5 production clusters and growing • Mix SSD and SATA clusters • Billions of page views per month
  • 4. With lots of patches Designing for EC2 • CDH 4.2.x • HDFS-3912 • HBase 0.94.7 • HBASE-8284 • One zone per cluster / no rack locality • RegionServers - Ephemeral disk only • Redundant clusters for availability • HDFS-4721 • HDFS-3703 • HDFS-9503 • HBASE-8389• HBASE-8434 • HBASE-7878
  • 5. Configuration Cluster Setup • Managed splitting w/pre split tables • Bloom filters for pretty much everything • Manual / Rolling major compactions • Reverse DNS on EC2 • 3 ZooKeepers in quorum • 1 NameNode / Sec-NameNode / Master • 1 EBS volume for fsImage / 1 Elastic IP • 10-50 nodes per cluster
  • 6. Fact-driven “Fry” method using Puppet Provisioning • User-data passed in to drive config management • Repackaged modifications to HDFS / HBase • Ubuntu .deb packages created with FPM • Synced to S3, nodes configured with s3-apt plugin • Mount + format ephemerals on boot • Ext4 / nodiratime / nodealloc / lazy_itable_init
  • 7. ---- HBASE MODULE ---- class { 'hbase': cluster => 'feeds_e', namenode => 'ec2-xxx-xxx-xxx-xxx.compute-1.amazonaws.com', zookeeper_quorum => 'zk1,zk2,zk3', hbase_site_opts => { 'hbase.replication' => true, 'hbase.snapshot.enabled' => true, 'hbase.snapshot.region.timeout' => '35000', 'replication.sink.client.ops.timeout' => '20000', 'replication.sink.client.retries.number' => '3', 'replication.source.size.capacity' => '4194304', 'replication.source.nb.capacity' => '100', ... } } ---- FACT BASED VARIABLES ---- $hbase_heap_size = $ec2_instance_type ? { 'hi1.4xlarge' => '24000', 'm2.2xlarge' => '24000', 'm2.xlarge' => '11480', 'm1.xlarge' => '11480', 'm1.large' => '6500', ... } Puppet Module
  • 8. Designed for EC2 Service Monitoring • Wounded (dying) vs Operational • High value metrics first • Overall health • Alive / dead nodes • Service up/down • Fsck / Blocks / % Space • Replication status • Regions needing splits • fsImage checkpoint • Zookeeper quorum • Synthetic transactions (get / put) • Queues (flush / compaction / rpc) • Latency (client / filesystem)
  • 10. Instrumentation Metrics • OpenTSDB for high cardinality metrics • Per region stats collection • tCollector • RegionServer HTTP JMX • HBase REST • GangliaContext for hadoop-metrics
  • 15. S3 + HBase Snapshots Backups • Full NameNode backup every 60 mins • EBS Volume as an name.dir for crash recovery • HBase snapshots + ExportSnapShot
  • 16. Additional Tuning Solid State Clusters • Lower block size down from 32k • Something a lot smaller. 8-16k • Placement groups for 10Gb networking • Increase DFSBandwidthPerSec • Kernel tuning for TCP • Compaction threads • Disk elevator to noop
  • 17. Process Planning for Launch • Pyres queue asynchronous reads / writes • Allows for tuning a system before it goes live • Tuning • Schema • Hot spots • Compaction • Canary roll out to new users • 10% -> 30% -> 80% -> 100%