Keep your Hadoop cluster at its best!

1 © Hortonworks Inc. 2011 – 2016. All Rights Reserved

Keep your Hadoop cluster at its best!Chris Nauroth Sheetal DolasHadoop Summit, San Jose, 2016


About Us

⬢  Principal Engineer @ Hortonworks

⬢  Committer and PMC, Apache Hadoop

–  Key contributor to HDFS ACLs, Windows compaJbility, and operability improvements

⬢  Hadoop user since 2010

–  Experience deploying, maintaining and using Hadoop clusters

[email protected]

cnauroth

Chris Nauroth


About Us

⬢  SmartSense Engineering Lead @ Hortonworks

⬢  Most of the career has been in the field, solving real life business problems

⬢  Last 6+ years in Big Data

⬢  Committer and PMC, Apache Metron

[email protected]

sheetal_dolas

Sheetal Dolas


Agenda

⬢  Days in a life of Hadoop users – Real war stories!

⬢  Hadoop Operational Challenges

⬢  Winning and avoiding the wars

⬢  Q & A


Days in a life of Hadoop users��Real war stories!


Story I: Unstable NameNode, Frequent Fail Overs

⬢  NameNode periodically becomes unresponsive

⬢  In HA scenario, fails over to standby

⬢  In short time, falls back again

⬢  Very frequent fail overs and fail backs

It was the garbage collection!


Story II: Very high CPU usage but low throughput

⬢  Unusually high system CPU usage

⬢  Jobs slowed down

⬢  Reduced data IO

System CPU

User CPU N/W IO

Transparent Huge Pages (THP) was turned on!


Job Perfor

mance

Cluster Stability

Story III: Cascading impact and cluster melt down

⬢  HDFS upgraded

⬢  HDFS utilization kept on increasing even after large data deletion

⬢  Rebalancing made the situation worse

⬢  Eventually HDFS became unresponsive

un-finalized HDFS had cascading impact on cluster!


Story IV: Overloaded cluster

⬢  Jobs run slower

⬢  Always waiting containers and jobs, all YARN queues are fully utilized

⬢  Some jobs had to wait for hours to get the container slots

Sub optimally configured container sizes!

Requested Memory

Used Memory


Story V: Accidental deletion of critical datasets

⬢  User accidentally executed hdfs dfs -rm -R on a root directory

⬢  Delete is issued in parallel, control + c did not help

⬢  In panic, user shuts down HDFS immediately (fortunately)

⬢  Restarts later to check trash, loses all data

⬢  It’s nearly impossible to recover blocks from local file system

This is a more common mistake than one may think!


Story VI: Hive query returning random results

⬢  A hive query returns different results every time

⬢  Results are usually accurate during office hours

⬢  After office hours, results keep changing randomly on every execution

-- QUERY: WHAT IS TODAY’S TOTAL SALE AS OF NOW ? SELECT SUM(amount) FROM sales WHERE sale_date = TO_DATE (UNIX_TIMESTAMP())

One of the host had a different time zone!


and the stories continue…

Hadoop operational challenges


Hadoop has lots of configurations

⬢  So many configurations! Overwhelming for many users

⬢  Best practices are evolving and change across versions


Many configurations are cluster and workload specific

⬢  A configuration good for one cluster may not be suitable for another cluster

⬢  Optimally configured clusters may become sub optimal tomorrow as they grow


Large clusters add to the complexities

⬢  Managing, updating and keeping nodes in sync becomes challenging

⬢  Nodes going down miss the maintenance cycles and get out of sync

⬢  Newly added nodes may have different standards (java version, os, user configurations etc.)

⬢  Clusters start having heterogeneous hardware over period of time


Winning ��and��avoiding��the wars with SmartSense


⬢  Proactive support & personalized cluster insights by

–  Enabling faster case resoluJon

–  Applying industry best pracJces

–  Providing proacJve analysis

⬢  SmartSense is a collection of tools and services

–  Evaluates cluster’s current configuraJon and runJme environment against rich set of rules

–  Rules are dynamic, reacJng to thresholds tailored to the specific cluster and its workloads

–  ConJnuously evolving and improving rule sets, developed by or in close consultaJon with acJve commiWers, support engineers, field engineers.

SmartSense


AGENT AGENT

AGENT AGENT AGENT

AGENT

LANDING ZONE

SERVER

AMBARI

AGENT AGENT

AGENT AGENT AGENT

AGENT

BUNDLE

WORKER NODE

WORKER NODE

WORKER NODE

WORKER NODE

WORKER NODE

WORKER NODE

SmartSense AnalyJcs

SmartSense Architecture

GATEWAY


Addressing: Unstable NameNode, Frequent Fail Overs

Daunting Questions

⬢  What is right Heap size for my NN ?

⬢  What should be the new gen size ?

⬢  Which GC should I use ?

⬢  What GC options to be configured?

⬢  What if my cluster grows ?

SmartSense Answer

⬢  Rule: hdfs_nn_jvm_opts

⬢  Calculates Heap size based on–  Current heap usage –  Total number of objects in file system –  Best pracJces

⬢  Recalculates dependent JVM options based on Heap size

⬢  Validates existing JVM opts

⬢  Provides continuous validations and proactive recommendations


Ã  Heap Size

–  200 bytes per HDFS object (files, directories, blocks)

–  25 % buffer

Ã  -Xms should be same as –Xmx

Ã  New generation size should be 1/8th of –Xmx (capped at 8G)

Ã  Use Concurrent Mark Sweep (CMS) Garbage Collection

–  -XX:+UseConcMarkSweepGC

–  -XX:CMSInitiatingOccupancyFraction=70

–  -XX:+UseCMSInitiatingOccupancyOnly

–  -XX:ParallelGCThreads=8

NameNode JVM Opts


Addressing: Very high CPU usage but low throughput

Daunting Questions

⬢  Is THP applicable to my OS version ?

⬢  Is it disabled ? Completely disabled ?

⬢  How do I make sure it is disabled on newly added nodes too ?

⬢  How do I make these configurations person independent ?

SmartSense Answer

⬢  Rule: os_thp

⬢  Checks if thp is completely disabled

⬢  Provides OS specific disabling instructions

⬢  Continuous evaluation that validates newly added nodes and re-commissioned nodes


Disable THP

⬢  For RedHat & CentOS

echo "never" > /sys/kernel/mm/redhat_transparent_hugepage/enabled

⬢  For Debian, Ubuntu & SUSE

echo "never" > /sys/kernel/mm/transparent_hugepage/enabled

System CPU

User CPU

N/W IO


Addressing: Cascading impact and cluster melt down

Daunting Questions

⬢  Should I finalize upgrade ?

⬢  What is right time to finalize ?

⬢  How do I make sure it does not fall through cracks ?

SmartSense Answer

⬢  Rule: hdfs_nn_finalize_upgrade

⬢  Checks HDFS health after upgrade

⬢  Evaluates how long HDFS is running in un-finalized state

⬢  Reminds until it is finalized


Ã  Check NN UI / JMX for upgrade status

Ã  Do not finalize HDFS upgrade until–  All files and blocks have been verified after upgrade

–  Critical jobs have been executed at least once after upgrade

Ã  Finalize between 2 - 7 days after upgrade

hdfs dfsadmin -finalizeUpgrade

HDFS Upgrade finalization


Addressing : Overloaded cluster

Daunting Questions

⬢  What is right container size for my cluster ?

⬢  If I add additional components (HBase, Storm), how does the container size change ?

⬢  How does container sizes change when I add new types of nodes in the cluster ?

⬢  What’s impact on container sizes if I add SSDs to the nodes?

SmartSense Answer

⬢  Rules: yarn_container_size, mr_container_size, tez_container_size

⬢  Evaluates resources available on individual host (CPU, Memory, Disks, Running Services etc.)

⬢  Calculates technology specific container sizes (MR, Tez, Hive)

⬢  Continuously evaluates as the cluster dynamics change


Container sizing

Ã  Identify resources (CPU, Memory, Disks) available on each node

Ã  Keep aside resources required for other processes (OS, DN, NM, HBase RS)

Ã  Calculate max possible containers for each resource (CPU, Memory, Disks)

–  CPU Containers: 4x cores

–  Disk Containers: ( 3x HDD + 10x SSD )

–  Memory Containers: (Available RAM / 2 )

Ã  Number of containers = Min (CPU Containers, Disk Containers, Memory Containers)


Addressing: Accidental deletion of critical datasets

Daunting Questions

⬢  Is HDFS trash enabled ?

⬢  What is safe trash interval ?

⬢  How to prevent accidental deletion of critical data ?

SmartSense Answer

⬢  Rule: hdfs_trash_interval–  Checks if trash is enabled –  Validates if trash interval is within

reasonable limits

⬢  Rule: hdfs_nn_protect_imp_dirs–  New feature available in Hadoop 2.8 –  Helps you mark criJcal directories such

as “/”, “/user”, “/user/apps/hive”, “/user/apps/hbase” etc. are delete protected.


HDFS Trash interval and directory protection

Ã  fs.trash.interval detects number of minutes after which the trashed data gets deleted

–  0 means trash disabled (data gets deleted immediately)

–  Keep it the range 1440 (1 day) – 10080 (7 days)

–  Recommended 4320 (3 days)

Ã  fs.protected.directories specifies directories that will be delete protected

–  Available from Hadoop 2.8

–  List all key directories there ("/", "/user","/user/apps", "/user/apps/hive", "/user/apps/hbase", "/user/apps/hbase/data", "/mapred", "/mapred/system", "/tmp" etc. )


Addressing : Hive query returning random results

Daunting Questions

⬢  Is my cluster configured consistently ?

⬢  How do I prevent such hard to analyze issues ?

⬢  How do I make sure newly added do not bring these types of issues ?

⬢  How do I make these set ups person independent ?

SmartSense Answer

⬢  Rule: os_time_zone

⬢  Checks if all hosts have same time zone

⬢  Rule os_service_ntpd_on make sure all host times are in sync

⬢  Continuous evaluation that validates newly added nodes and re-commissioned nodes


There are 250+ more such rulesOperationsÃ  hdfs_dn_volume_tolerance Ã  hdfs_dn_xceivers Ã  hdfs_nn_handler_countÃ  …Ã  yarn_zk_quorum Ã  yarn_nm_recovery Ã  …Ã  os_hostname_reverse_lookup Ã  os_ssd_tuningÃ  …Ã  hive_mr_strict_mode Ã  hive_datanucleus_cache Ã  …Ã  tez_am_heap Ã  tez_shuffle_buffer Ã  …

PerformanceÃ  ams_mc_distributed_configsÃ  ams_mc_write_pathÃ  ...Ã  hbase_jvm_optsÃ  hbase_rs_open_region_threadsÃ  hbase_tcp_nodelayÃ  ...Ã  hdfs_dn_jvm_optsÃ  hdfs_mount_optionsÃ  hdfs_nn_dn_staleness_intervalÃ  ...Ã  hive_auto_convert_joinÃ  hive_disable_cachingÃ  hive_enable_cboÃ  ...

SecurityÃ  hdfs_dn_volume_tolerance Ã  hdfs_audit_logÃ  hdfs_block_access_tokenÃ  hdfs_enable_security_checkÃ  hdfs_nn_super_user_groupÃ  hdfs_zkfc_ha_aclÃ  ...Ã  ranger_policy_refresh_intervalÃ  smartsense_2_way_ssl_enabledÃ  ...Ã  yarn_ats_securityÃ  yarn_enable_aclÃ  ...


There is more than just configurations

How do I show back/charge back my tenants ?

Who are the top users of

my platform ?What type of

work loads are running on my

cluster ?

Which jobs have significant impact on my

cluster ?

How do I improve

performance of key jobs ?

What is good time for

maintenance?


Activity Analysis


Summary

Ã  There are many things involved in managing Hadoop cluster

Ã  Best practices evolve and change across versions

Ã  What is optimal today may not be optimal for tomorrow

Ã  Changing cluster dynamics, workload characteristic need continuous re-evaluation and configuration adjustments

Ã  SmartSense can significantly help avoid common mistakes, issues, pitfalls and simplify Hadoop operations


Lets keep your Hadoop cluster at its best!Thank You!


Appendix


More Resources

⬢  https://docs.hortonworks.com/index.html

⬢  http://hortonworks.com/products/subscriptions/smartsense/

⬢  http://hortonworks.com/info/smartsense/

⬢  http://hortonworks.com/blog/introducing-hortonworks-smartsense/

⬢  https://www.youtube.com/watch?v=IKulo9c8PjE

⬢  https://community.hortonworks.com/topics/smartsense.html


SmartSense Bundle Security

⬢  All Bundles are Anonymized and Encrypted

⬢  MulJple built-‐in security measures

–  Ambari clear text passwords are not collected

–  Hive and Oozie database properties are not collected

–  All IP addresses and host names are anonymized

⬢  Extensible security rules –  Exclude properties within specific Hadoop configuration files

–  Global REGEX replacements across all configuration, metrics, and logs


SmartSense Stack Support

HDP 2.4 HDP 2.3 HDP 2.2 HDP 2.1 HDP 2.0

SmartSense 1.x

Ambari 2.2Built-In!

Ambari 2.1Plug-In

Ambari 2.0Plug-In

Ambari 1.7 Ambari 1.6

SmartSense 1.x

Technology

Keep your Hadoop cluster at its best!