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From Apache Wiki <wikidi...@apache.org>
Subject [Hadoop Wiki] Update of "Hbase/Troubleshooting" by GabrielReid
Date Wed, 08 Dec 2010 09:21:54 GMT
Dear Wiki user,

You have subscribed to a wiki page or wiki category on "Hadoop Wiki" for change notification.

The "Hbase/Troubleshooting" page has been changed by GabrielReid.
The comment on this change is: Added information about scans or MapReduce jobs failing over
a large table with many regions.
http://wiki.apache.org/hadoop/Hbase/Troubleshooting?action=diff&rev1=44&rev2=45

--------------------------------------------------

  == Contents ==
-  1. [[#1|Problem: Master initializes, but Region Servers do not]]
+  1. [[#A1|Problem: Master initializes, but Region Servers do not]]
-  1. [[#2|Problem: Created Root Directory for HBase through Hadoop DFS]]
+  1. [[#A2|Problem: Created Root Directory for HBase through Hadoop DFS]]
-  1. [[#3|Problem: Replay of hlog required, forcing regionserver restart]]
+  1. [[#A3|Problem: Replay of hlog required, forcing regionserver restart]]
-  1. [[#4|Problem: On migration, no files in root directory]]
+  1. [[#A4|Problem: On migration, no files in root directory]]
-  1. [[#5|Problem: "xceiverCount 258 exceeds the limit of concurrent xcievers 256"]]
+  1. [[#A5|Problem: "xceiverCount 258 exceeds the limit of concurrent xcievers 256"]]
-  1. [[#6|Problem: "No live nodes contain current block"]]
+  1. [[#A6|Problem: "No live nodes contain current block"]]
-  1. [[#7|Problem: DFS instability and/or regionserver lease timeouts]]
+  1. [[#A7|Problem: DFS instability and/or regionserver lease timeouts]]
-  1. [[#8|Problem: Instability on Amazon EC2]]
+  1. [[#A8|Problem: Instability on Amazon EC2]]
-  1. [[#9|Problem: Zookeeper SessionExpired events]]
+  1. [[#A9|Problem: Zookeeper SessionExpired events]]
-  1. [[#10|Problem: Scanners keep getting timeouts]]
+  1. [[#A10|Problem: Scanners keep getting timeouts]]
-  1. [[#11|Problem: Client says no such table but it exists]]
+  1. [[#A11|Problem: Client says no such table but it exists]]
-  1. [[#12|Problem: Could not find my address: xyz in list of ZooKeeper quorum servers]]
+  1. [[#A12|Problem: Could not find my address: xyz in list of ZooKeeper quorum servers]]
-  1. [[#13|Problem: Long client pauses under high load; or deadlock if using THBase]]
+  1. [[#A13|Problem: Long client pauses under high load; or deadlock if using THBase]]
-  1. [[#14|Problem: Zookeeper does not seem to work on Amazon EC2]]
+  1. [[#A14|Problem: Zookeeper does not seem to work on Amazon EC2]]
-  1. [[#15|Problem: General operating environment issues -- zookeeper session timeouts, regionservers
shutting down, etc.]]
+  1. [[#A15|Problem: General operating environment issues -- zookeeper session timeouts,
regionservers shutting down, etc.]]
-  1. [[#16|Problem: Scanner performance is low]]
+  1. [[#A16|Problem: Scanner performance is low]]
-  1. [[#17|Problem: My shell or client application throws lots of scary exceptions during
normal operation]]
+  1. [[#A17|Problem: My shell or client application throws lots of scary exceptions during
normal operation]]
-  1. [[#18|Problem: The HBase or Hadoop daemons crash after some days of uptime with no errors
logged]]
+  1. [[#A18|Problem: The HBase or Hadoop daemons crash after some days of uptime with no
errors logged]]
- 
+  1. [[#A19|Problem: Running a Scan or a MapReduce job over a full table fails with "xceiverCount
xx exceeds..." or OutOfMemoryErrors in the HDFS datanodes]]
  
  <<Anchor(1)>>
+ 
  == 1. Problem: Master initializes, but Region Servers do not ==
   * Master's log contains repeated instances of the following block:
+   . ~-INFO org.apache.hadoop.ipc.Client: Retrying connect to server: /127.0.0.1:60020. Already
tried 1 time(s).<<BR>> INFO org.apache.hadoop.ipc.Client: Retrying connect to
server: /127.0.0.1:60020. Already tried 2 time(s).<<BR>> -~
-   ~-INFO org.apache.hadoop.ipc.Client: Retrying connect to server: /127.0.0.1:60020. Already
tried 1 time(s).<<BR>>
-   INFO org.apache.hadoop.ipc.Client: Retrying connect to server: /127.0.0.1:60020. Already
tried 2 time(s).<<BR>>
-   ...<<BR>>
-   INFO org.apache.hadoop.ipc.RPC: Server at /127.0.0.1:60020 not available yet, Zzzzz...-~
+   . ~-..<<BR>> INFO org.apache.hadoop.ipc.RPC: Server at /127.0.0.1:60020 not
available yet, Zzzzz...-~
   * Region Servers' logs contains repeated instances of the following block:
+   . ~-INFO org.apache.hadoop.ipc.Client: Retrying connect to server: masternode/192.168.100.50:60000.
Already tried 1 time(s).<<BR>> INFO org.apache.hadoop.ipc.Client: Retrying connect
to server: masternode/192.168.100.50:60000. Already tried 2 time(s).<<BR>> -~
-   ~-INFO org.apache.hadoop.ipc.Client: Retrying connect to server: masternode/192.168.100.50:60000.
Already tried 1 time(s).<<BR>>
-   INFO org.apache.hadoop.ipc.Client: Retrying connect to server: masternode/192.168.100.50:60000.
Already tried 2 time(s).<<BR>>
-   ...<<BR>>
-   INFO org.apache.hadoop.ipc.RPC: Server at masternode/192.168.100.50:60000 not available
yet, Zzzzz...-~
+   . ~-..<<BR>> INFO org.apache.hadoop.ipc.RPC: Server at masternode/192.168.100.50:60000
not available yet, Zzzzz...-~
   * Note that the Master believes the Region Servers have the IP of 127.0.0.1 - which is
localhost and resolves to the master's own localhost.
+ 
  === Causes ===
   * The Region Servers are erroneously informing the Master that their IP addresses are 127.0.0.1.
+ 
  === Resolution ===
   * Modify '''/etc/hosts''' on the region servers, from
-   {{{
+   . {{{
  # Do not remove the following line, or various programs
  # that require network functionality will fail.
- 127.0.0.1		fully.qualified.regionservername regionservername  localhost.localdomain localhost
+ 127.0.0.1               fully.qualified.regionservername regionservername  localhost.localdomain
localhost
- ::1		localhost6.localdomain6 localhost6
+ ::1             localhost6.localdomain6 localhost6
  }}}
  
   * To (removing the master node's name from localhost)
-   {{{
+   . {{{
  # Do not remove the following line, or various programs
  # that require network functionality will fail.
- 127.0.0.1		localhost.localdomain localhost
+ 127.0.0.1               localhost.localdomain localhost
- ::1		localhost6.localdomain6 localhost6
+ ::1             localhost6.localdomain6 localhost6
  }}}
  
- 
- <<Anchor(2)>> 
+ <<Anchor(2)>>
+ 
  == 2. Problem: Created Root Directory for HBase through Hadoop DFS ==
   * On Startup, Master says that you need to run the hbase migrations script. Upon running
that, the hbase migrations script says no files in root directory.
+ 
  === Causes ===
   * HBase expects the root directory to either not exist, or to have already been initialized
by hbase running a previous time. If you create a new directory for HBase using Hadoop DFS,
this error will occur.
+ 
  === Resolution ===
   * Make sure the HBase root directory does not currently exist or has been initialized by
a previous run of HBase. Sure fire solution is to just use Hadoop dfs to delete the HBase
root and let HBase create and initialize the directory itself.
  
- 
  <<Anchor(3)>>
+ 
  == 3. Problem: Replay of hlog required, forcing regionserver restart ==
-  * Under a heavy write load, some regions servers will go down with the following exception:

+  * Under a heavy write load, some regions servers will go down with the following exception:
+ 
  {{{
  WARN org.apache.hadoop.dfs.DFSClient: Exception while reading from blk_xxxxxxxxxxxxxxx of
/hbase/some_repository from IP_address:50010: java.io.IOException: Premeture EOF from inputStream
  then later
@@ -81, +83 @@

  }}}
  === Causes ===
   * RPC timeouts may happen because of a IO contention which blocks processes during file
swapping.
+ 
  === Resolution ===
   * Configure your system to avoid swapping. Set vm.swappiness to 0. (http://kerneltrap.org/node/1044)
  
- 
  <<Anchor(4)>>
+ 
  == 4. Problem: On migration, no files in root directory ==
   * On Startup, Master says that you need to run the hbase migrations script. Upon running
that, the hbase migrations script says no files in root directory.
+ 
  === Causes ===
   * HBase expects the root directory to either not exist, or to have already been initialized
by hbase running a previous time. If you create a new directory for HBase using Hadoop DFS,
this error will occur.
+ 
  === Resolution ===
   * Make sure the HBase root directory does not currently exist or has been initialized by
a previous run of HBase. Sure fire solution is to just use Hadoop dfs to delete the HBase
root and let HBase create and initialize the directory itself.
  
- 
  <<Anchor(5)>>
+ 
  == 5. Problem: "xceiverCount 258 exceeds the limit of concurrent xcievers 256" ==
   * See an exception with above message in logs, usually the datanode logs.
+ 
  === Causes ===
   * An upper bound on connections was added in Hadoop (HADOOP-3633/HADOOP-3859).
+ 
  === Resolution ===
-  * Up the maximum by setting '''dfs.datanode.max.xcievers''' (sic).  See [[http://mail-archives.apache.org/mod_mbox/hadoop-hbase-user/200810.mbox/%3C20126171.post@talk.nabble.com%3E|message
from jean-adrien]] for some background. Values of 2048 or 4096 are common. 
+  * Up the maximum by setting '''dfs.datanode.max.xcievers''' (sic).  See [[http://mail-archives.apache.org/mod_mbox/hadoop-hbase-user/200810.mbox/<20126171.post@talk.nabble.com>|message
from jean-adrien]] for some background. Values of 2048 or 4096 are common.
- 
+  * This may be a symptom of having an unrealistically high number of regions in a table
and/or an underpowered cluster; see [[#A19|the discussion of this below]]
  
  <<Anchor(6)>>
+ 
  == 6. Problem: "No live nodes contain current block" ==
   * See an exception with above message in logs.
+ 
  === Causes ===
   * Insufficient file descriptors available at the OS level for DFS DataNodes
   * Patch for HDFS-127 is not present (Should not be an issue for HBase >= 0.20.0 as a
private Hadoop jar is shipped with the client side fix applied)
   * Slow datanodes are marked as down by DFSClient; eventually all replicas are marked as
'bad' (HADOOP-3831).
+ 
  === Resolution ===
-  * Increase the file descriptor limit of the user account under which the DFS DataNode processes
are operating. On most Linux systems, adding the following lines to /etc/security/limits.conf
will increase the file descriptor limit from the default of 1024 to 32768. Substitute the
actual user name for {{{<user>}}}. 
+  * Increase the file descriptor limit of the user account under which the DFS DataNode processes
are operating. On most Linux systems, adding the following lines to /etc/security/limits.conf
will increase the file descriptor limit from the default of 1024 to 32768. Substitute the
actual user name for {{{<user>}}}.
-    {{{
+   . {{{
  <user>          soft    nofile          32768
  <user>          hard    nofile          32768
  }}}
   * RedHat based distributions also may have a maximum total open files across the whole
system, so you will also need to edit /etc/sysctl.conf to include the line:
-    {{{
+   . {{{
  fs.file-max = 32768
  }}}
-   Run the commands {{{sysctl -p /etc/sysctl.conf}}} and {{{service network restart}}} to
make the change immediately effective.
+   . Run the commands {{{sysctl -p /etc/sysctl.conf}}} and {{{service network restart}}}
to make the change immediately effective.
- 
  
  <<Anchor(7)>>
+ 
  == 7. Problem: DFS instability and/or regionserver lease timeouts ==
   * HBase regionserver leases expire during start up
   * HBase daemons cannot find block locations in HDFS during start up or other periods of
load
   * HBase regionserver restarts after beeing unable to report to master:
+ 
  {{{
  2009-02-24 10:01:33,516 WARN org.apache.hadoop.hbase.util.Sleeper: We slept xxx ms, ten
times longer than scheduled: 10000
  2009-02-24 10:01:33,516 WARN org.apache.hadoop.hbase.util.Sleeper: We slept xxx ms, ten
times longer than scheduled: 15000
@@ -137, +148 @@

   * Slow host name resolution
   * Very long garbage collector task for the RegionServer JVM: The ''default garbage collector''
of the HotspotTM JavaTM Virtual Machine runs a ''full gc'' on the ''old space'' when the memory
space is full, which can represent about 90% of the allocated heap space. During this task,
the running program is stopped, the timers as well. If the heap space is mostly in the swap
partition, and moreover if it is larger than the physical memory, the subsequent swap can
yield to I/O overload and takes several minutes.
   * Network bandwidth overcommitment
+ 
  === Resolution ===
   * Insure that host name resolution latency is low, or use static entries in /etc/hosts
   * Monitor the network and insure that adequate bandwidth is available for HRPC transactions
   * In accordance with your hardware, tune your heap space / garbage collector settings in
the HBASE_OPTS variable of {{{$HBASE_CONF/hbase-env.sh}}}. Try the ''concurrent garbage collector''
{{{(-XX:+UseConcMarkSweepGC)}}} to avoid to stop the threads during GC. Read these articles
for more info about Hotspot GC settings
-     * [[http://java.sun.com/docs/hotspot/gc1.4.2/faq.html|Garbage collector FAQ]] Quick
overview
+   * [[http://java.sun.com/docs/hotspot/gc1.4.2/faq.html|Garbage collector FAQ]] Quick overview
-     * [[http://java.sun.com/javase/technologies/hotspot/gc/gc_tuning_6.html|Tuning garbage
collector in Java SE 6]]
+   * [[http://java.sun.com/javase/technologies/hotspot/gc/gc_tuning_6.html|Tuning garbage
collector in Java SE 6]]
   * For Java SE 6, some users have had success with {{{ -XX:+UseConcMarkSweepGC -XX:+CMSIncrementalMode
-XX:ParallelGCThreads=8 }}}.
   * See HBase [[PerformanceTuning|Performance Tuning]] for more on JVM GC tuning.
  
- 
  <<Anchor(8)>>
+ 
  == 8. Problem: Instability on Amazon EC2 ==
-  * Various problems suggesting overloading on Amazon EC2 deployments: Scanner timeouts,
problems locating HDFS blocks, missed heartbeats, "We slept xxx ms, ten times longer than
scheduled" messages, and so on. 
+  * Various problems suggesting overloading on Amazon EC2 deployments: Scanner timeouts,
problems locating HDFS blocks, missed heartbeats, "We slept xxx ms, ten times longer than
scheduled" messages, and so on.
-  * These problems continue after following the other relevant advice on this page. 
+  * These problems continue after following the other relevant advice on this page.
   * Or, you are trying to use Small or Medium instance types. (Do not.)
+ 
  === Causes ===
-  * Hadoop and HBase daemons require 1GB heap, therefore RAM, per daemon. For load intensive
environments, HBase regionservers may require more heap than this. There must be enough available
RAM to comfortably hold the working sets of all Java processes running on the instance. This
includes any mapper or reducer tasks which may run co-located with system daemons. Small and
Medium instances do not have enough available RAM to contain typical Hadoop+HBase deployments.

+  * Hadoop and HBase daemons require 1GB heap, therefore RAM, per daemon. For load intensive
environments, HBase regionservers may require more heap than this. There must be enough available
RAM to comfortably hold the working sets of all Java processes running on the instance. This
includes any mapper or reducer tasks which may run co-located with system daemons. Small and
Medium instances do not have enough available RAM to contain typical Hadoop+HBase deployments.
-  * Hadoop and HBase daemons are latency sensitive. There should be enough free RAM so no
swapping occurs. Swapping during garbage collection may cause JVM threads to be suspended
for a critically long time. Also, there should be sufficient virtual cores to service the
JVM threads whenever they become runnable. Large instances have two virtual cores, so they
can run HDFS and HBase daemons concurrently, but nothing more. X-Large instances have four
virtual cores, so they can run in addition to HDFS and HBase daemons two mappers or reducers
concurrently. Configure TaskTracker concurrency limits accordingly, or separate mapreduce
computation from storage functions. 
+  * Hadoop and HBase daemons are latency sensitive. There should be enough free RAM so no
swapping occurs. Swapping during garbage collection may cause JVM threads to be suspended
for a critically long time. Also, there should be sufficient virtual cores to service the
JVM threads whenever they become runnable. Large instances have two virtual cores, so they
can run HDFS and HBase daemons concurrently, but nothing more. X-Large instances have four
virtual cores, so they can run in addition to HDFS and HBase daemons two mappers or reducers
concurrently. Configure TaskTracker concurrency limits accordingly, or separate mapreduce
computation from storage functions.
+ 
  === Resolution ===
   * Use X-Large (c1.xlarge) instances
-  * Consider splitting storage and computational function over disjoint instance sets. 
+  * Consider splitting storage and computational function over disjoint instance sets.
- 
  
  <<Anchor(9)>>
+ 
  == 9. Problem: ZooKeeper SessionExpired events ==
   * Master or Region Servers shutting down with messages like those in the logs:
+ 
  {{{
- WARN org.apache.zookeeper.ClientCnxn: Exception 
+ WARN org.apache.zookeeper.ClientCnxn: Exception
  closing session 0x278bd16a96000f to sun.nio.ch.SelectionKeyImpl@355811ec
  java.io.IOException: TIMED OUT
         at org.apache.zookeeper.ClientCnxn$SendThread.run(ClientCnxn.java:906)
@@ -183, +198 @@

   * The JVM is doing a long running garbage collecting which is pausing every threads (aka
"stop the world").
   * Since the region server's local zookeeper client cannot send heartbeats, the session
times out.
   * By design, we shut down any node that isn't able to contact the Zookeeper ensemble after
getting a timeout so that it stops serving data that may already be assigned elsewhere.
+ 
  === Resolution ===
   * Make sure you give plenty of RAM (in hbase-env.sh), the default of 1GB won't be able
to sustain long running imports.
   * Make sure you don't swap, the JVM never behaves well under swapping.
-  * Make sure you are not CPU starving the region server thread. For example, if you are
running a mapreduce job using 6 CPU-intensive tasks on a machine with 4 cores, you are probably
starving the region server enough to create longer garbage collection pauses. 
+  * Make sure you are not CPU starving the region server thread. For example, if you are
running a mapreduce job using 6 CPU-intensive tasks on a machine with 4 cores, you are probably
starving the region server enough to create longer garbage collection pauses.
   * If you wish to increase the session timeout, add the following to your hbase-site.xml
to increase the timeout from the default of 60 seconds to 120 seconds.
+ 
  {{{
    <property>
      <name>zookeeper.session.timeout</name>
@@ -198, +215 @@

      <value>6000</value>
    </property>
  }}}
-  * Be aware that setting a higher timeout means that the regions served by a failed region
server will take at least that amount of time to be transfered to another region server. For
a production system serving live requests, we would instead recommend setting it lower than
1 minute and over-provision your cluster in order the lower the memory load on each machines
(hence having less garbage to collect per machine). 
+  * Be aware that setting a higher timeout means that the regions served by a failed region
server will take at least that amount of time to be transfered to another region server. For
a production system serving live requests, we would instead recommend setting it lower than
1 minute and over-provision your cluster in order the lower the memory load on each machines
(hence having less garbage to collect per machine).
   * If this is happening during an upload which only happens once (like initially loading
all your data into HBase), consider [[http://hadoop.apache.org/hbase/docs/r0.20.3/api/org/apache/hadoop/hbase/mapreduce/package-summary.html#bulk|importing
into HFiles directly]].
   * HBase ships with some GC tuning, for more information see [[PerformanceTuning|Performance
Tuning]].
  
- 
  <<Anchor(10)>>
+ 
  == 10. Problem: Scanners keep getting timeouts ==
   * Client receives org.apache.hadoop.hbase.UnknownScannerException or timeouts even if the
region server lease is really high. Fixed in HBase 0.20.0
+ 
  === Causes ===
   * The client, by default, fetches 30 rows when issuing the first next(). All the 29 other
calls simply return rows from local memory. So if it takes 3 minutes to process a row and
the timeout is set to 30 minutes, it is still not enough to cover 30 * 3 = 90 minutes.
+ 
  === Resolution ===
   * Set hbase.client.scanner.caching in hbase-site.xml at a very low value like 1 or use
HTable.setScannerCaching(1).
  
- 
  <<Anchor(11)>>
+ 
  == 11. Problem: Client says no such table but it exists ==
   * Client can't find region in table, says no such table.
+ 
  === Causes ===
   * Just deleted a large table
+ 
  === Resolution ===
   * Run major compaction on the .META. table.  In the shell, type '''tool''' to learn how
to run a major compaction from the shell.
  
- 
  <<Anchor(12)>>
+ 
  == 12. Problem: Could not find my address: xyz in list of ZooKeeper quorum servers ==
   * A Zookeeper server wasn't able to start, throws that error. xyz is the name of your server.
+ 
  === Causes ===
   * This is a name lookup problem. HBase tries to start a ZK server on some machine but that
machine isn't able to find itself in the '''hbase.zookeeper.quorum configuration'''.
+ 
  === Resolution ===
   * Use the hostname presented in the error message instead of the value you used. If you
have a DNS server, you can set '''hbase.zookeeper.dns.interface''' and '''hbase.zookeeper.dns.nameserver'''
in hbase-site.xml to make sure it resolves to the correct FQDN.
  
- 
  <<Anchor(13)>>
+ 
  == 13. Problem: Long client pauses under high load; or deadlock if using transactional HBase
(THBase) ==
   * Under high load, some client operations take a long time; waiting appears uneven
   * If using THBase, apparent deadlocks: for example, in thread dumps IPC Server handlers
are blocked in org.apache.hadoop.hbase.regionserver.tableindexed.IndexedRegion.updateIndex()
+ 
  === Causes ===
   * The default number of regionserver RPC handlers is insufficient.
+ 
  === Resolution ===
   * Increase the value of "hbase.regionserver.handler.count" in hbase-site.xml. The default
is 10. Try 100.
  
- 
  <<Anchor(14)>>
+ 
  == 14. Problem: Zookeeper does not seem to work on Amazon EC2 ==
   * HBase does not start when deployed as Amazon EC2 instances.
   * Exceptions like the below appear in the master and/or region server logs:
+ 
  {{{
    2009-10-19 11:52:27,030 INFO org.apache.zookeeper.ClientCnxn: Attempting
    connection to server ec2-174-129-15-236.compute-1.amazonaws.com/10.244.9.171:2181
@@ -253, +279 @@

  }}}
  === Causes ===
   * Security group policy is blocking the Zookeeper port on a public address.
+ 
  === Resolution ===
-  * Use the internal EC2 host names when configuring the Zookeeper quorum peer list. 
+  * Use the internal EC2 host names when configuring the Zookeeper quorum peer list.
- 
  
  <<Anchor(15)>>
+ 
  == 15. Problem: General operating environment issues -- zookeeper session timeouts, regionservers
shutting down, etc ==
  === Causes ===
-  Various.
+  . Various.
+ 
  === Resolution ===
  See the [[http://wiki.apache.org/hadoop/ZooKeeper/Troubleshooting|ZooKeeper Operating Environment
Troubleshooting]] page.  It has suggestions and tools for checking disk and networking performance;
i.e. the operating environment your zookeeper and hbase are running in.  ZooKeeper is the
cluster's "canary".  It'll be the first to notice issues if any so making sure its happy is
the short-cut to a humming cluster.
  
- 
  <<Anchor(16)>>
+ 
  == 16. Problem: Scanner performance is low ==
  === Causes ===
  Default scanner caching (prefetching) is set to 1. The default is low because if a job takes
too long processing, a scanner can time out, which causes unhappy jobs/people/emails. See
item #10 above.
+ 
  === Resolution ===
   * Increase the amount of prefetching on the scanner, to 10, or 100, or 1000, as appropriate
for your workload: [[http://hadoop.apache.org/hbase/docs/current/api/org/apache/hadoop/hbase/client/HTable.html#scannerCaching|HTable.scannerCaching]]
   * This change can be accomplished globally by setting the hbase.client.scanner.caching
property in hbase-site.xml to the desired value.
  
- 
  <<Anchor(17)>>
+ 
  == 17. Problem: My shell or client application throws lots of scary exceptions during normal
operation ==
  === Causes ===
  Since 0.20.0 the default log level for org.apache.hadoop.hbase.* is DEBUG.
+ 
  === Resolution ===
+ On your clients, edit $HBASE_HOME/conf/log4j.properties and change this: {{{log4j.logger.org.apache.hadoop.hbase=DEBUG}}}
to this: {{{log4j.logger.org.apache.hadoop.hbase=INFO}}}, or even {{{log4j.logger.org.apache.hadoop.hbase=WARN}}}
.
- On your clients, edit $HBASE_HOME/conf/log4j.properties and change this: {{{log4j.logger.org.apache.hadoop.hbase=DEBUG}}}
- to this: {{{log4j.logger.org.apache.hadoop.hbase=INFO}}}, or even {{{log4j.logger.org.apache.hadoop.hbase=WARN}}}
.
  
  <<Anchor(18)>>
+ 
  == 18. Problem: The HBase or Hadoop daemons crash after some days of uptime with no errors
logged ==
  === Causes ===
  HBase and Hadoop have stability issues on certain versions of the JVM that can cause this
issue. In particular, Sun Java 1.6.0_18 is known to be buggy. The current recommended version
for production usage is 1.6.0_16.
+ 
  === Resolution ===
  Downgrade your JVM to 1.6.0_16.
  
+ <<Anchor(19)>>
+ 
+ == 19. Problem: Running a Scan or a MapReduce job over a full table fails with "xceiverCount
xx exceeds..." or OutOfMemoryErrors in the HDFS datanodes ==
+ 
+ === Causes ===
+ HBase keeps a number of files per region open on HDFS. When you have a large number of regions
in a single table, this means that HDFS needs to keep a large number of files open on HDFS,
which can cause you to run into the [[#A5|"xceiverCount xx exceeds..."]] issue, or conversely
``OutOfMemoryErrors due to raising the '''dfs.datanode.max.xceivers''' setting too high to
escape this issue.
+ 
+ Each region in HBase corresponds to 0 to N store files in HDFS. The '''dfs.datanode.max.xcievers'''
setting controls the maximum number of handler threads that are allowed per HDFS datanode.
Each store file consumes at least one thread on the datanode. Once a store file is opened,
it stays open until a compaction or splitting is needed; this can result in the dfs.datanode.max.xceivers
limit being reached surprisingly quickly if you have a lot of regions in a single table.
+ 
+ This problem is generally a symptom of an underpowered cluster. 
+ 
+ === Resolution ===
+ 
+ This can be resolved in the following ways:
+  * Increase the maximum file size per region; this is the '''hbase.hregion.max.filesize'''
in hbase-site.xml, and it defaults to 268435456 (256 MB). Keep in mind that this will only
apply to future region splits, and will not result in existing regions being merged.
+  * Mess with configuration that effects RAM -- i.e. thread stack sizes or, dependent on
what your query path looks like, shrink size given over to block cache (will slow your reads
though)
+  * Add machines to your cluster.
+ 

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