diff --git a/src/docbkx/book.xml b/src/docbkx/book.xml
index 59b18cd3739..9b1a0e92c47 100644
--- a/src/docbkx/book.xml
+++ b/src/docbkx/book.xml
@@ -2396,6 +2396,7 @@ myHtd.setValue(HTableDescriptor.SPLIT_POLICY, MyCustomSplitPolicy.class.getName(
+
diff --git a/src/docbkx/case_studies.xml b/src/docbkx/case_studies.xml
new file mode 100644
index 00000000000..c0b8c6d2fcf
--- /dev/null
+++ b/src/docbkx/case_studies.xml
@@ -0,0 +1,179 @@
+
+
+
+ Case Studies
+
+ Overview
+ This chapter will describe a variety of performance and troubleshooting case studies that can
+ provide a useful blueprint on diagnosing cluster issues.
+ For more information on Performance and Troubleshooting, see and .
+
+
+
+
+ Case Study #1 (Performance Issue On A Single Node)
+ Scenario
+ Following a scheduled reboot, one data node began exhibiting unusual behavior. Routine MapReduce
+ jobs run against HBase tables which regularly completed in five or six minutes began taking 30 or 40 minutes
+ to finish. These jobs were consistently found to be waiting on map and reduce tasks assigned to the troubled data node
+ (e.g., the slow map tasks all had the same Input Split).
+ The situation came to a head during a distributed copy, when the copy was severely prolonged by the lagging node.
+
+
+ Hardware
+ Datanodes:
+
+ Two 12-core processors
+ Six Enerprise SATA disks
+ 24GB of RAM
+ Two bonded gigabit NICs
+
+
+ Network:
+
+ 10 Gigabit top-of-rack switches
+ 20 Gigabit bonded interconnects between racks.
+
+
+
+ Hypotheses
+ HBase "Hot Spot" Region
+ We hypothesized that we were experiencing a familiar point of pain: a "hot spot" region in an HBase table,
+ where uneven key-space distribution can funnel a huge number of requests to a single HBase region, bombarding the RegionServer
+ process and cause slow response time. Examination of the HBase Master status page showed that the number of HBase requests to the
+ troubled node was almost zero. Further, examination of the HBase logs showed that there were no region splits, compactions, or other region transitions
+ in progress. This effectively ruled out a "hot spot" as the root cause of the observed slowness.
+
+
+ HBase Region With Non-Local Data
+ Our next hypothesis was that one of the MapReduce tasks was requesting data from HBase that was not local to the datanode, thus
+ forcing HDFS to request data blocks from other servers over the network. Examination of the datanode logs showed that there were very
+ few blocks being requested over the network, indicating that the HBase region was correctly assigned, and that the majority of the necessary
+ data was located on the node. This ruled out the possibility of non-local data causing a slowdown.
+
+
+ Excessive I/O Wait Due To Swapping Or An Over-Worked Or Failing Hard Disk
+ After concluding that the Hadoop and HBase were not likely to be the culprits, we moved on to troubleshooting the datanode's hardware.
+ Java, by design, will periodically scan its entire memory space to do garbage collection. If system memory is heavily overcommitted, the Linux
+ kernel may enter a vicious cycle, using up all of its resources swapping Java heap back and forth from disk to RAM as Java tries to run garbage
+ collection. Further, a failing hard disk will often retry reads and/or writes many times before giving up and returning an error. This can manifest
+ as high iowait, as running processes wait for reads and writes to complete. Finally, a disk nearing the upper edge of its performance envelope will
+ begin to cause iowait as it informs the kernel that it cannot accept any more data, and the kernel queues incoming data into the dirty write pool in memory.
+ However, using vmstat(1) and free(1), we could see that no swap was being used, and the amount of disk IO was only a few kilobytes per second.
+
+
+ Slowness Due To High Processor Usage
+ Next, we checked to see whether the system was performing slowly simply due to very high computational load. top(1) showed that the system load
+ was higher than normal, but vmstat(1) and mpstat(1) showed that the amount of processor being used for actual computation was low.
+
+
+ Network Saturation (The Winner)
+ Since neither the disks nor the processors were being utilized heavily, we moved on to the performance of the network interfaces. The datanode had two
+ gigabit ethernet adapters, bonded to form an active-standby interface. ifconfig(8) showed some unusual anomalies, namely interface errors, overruns, framing errors.
+ While not unheard of, these kinds of errors are exceedingly rare on modern hardware which is operating as it should:
+
+$ /sbin/ifconfig bond0
+bond0 Link encap:Ethernet HWaddr 00:00:00:00:00:00
+inet addr:10.x.x.x Bcast:10.x.x.255 Mask:255.255.255.0
+UP BROADCAST RUNNING MASTER MULTICAST MTU:1500 Metric:1
+RX packets:2990700159 errors:12 dropped:0 overruns:1 frame:6 <--- Look Here! Errors!
+TX packets:3443518196 errors:0 dropped:0 overruns:0 carrier:0
+collisions:0 txqueuelen:0
+RX bytes:2416328868676 (2.4 TB) TX bytes:3464991094001 (3.4 TB)
+
+
+ These errors immediately lead us to suspect that one or more of the ethernet interfaces might have negotiated the wrong line speed. This was confirmed both by running an ICMP ping
+ from an external host and observing round-trip-time in excess of 700ms, and by running ethtool(8) on the members of the bond interface and discovering that the active interface
+ was operating at 100Mbs/, full duplex.
+
+$ sudo ethtool eth0
+Settings for eth0:
+Supported ports: [ TP ]
+Supported link modes: 10baseT/Half 10baseT/Full
+ 100baseT/Half 100baseT/Full
+ 1000baseT/Full
+Supports auto-negotiation: Yes
+Advertised link modes: 10baseT/Half 10baseT/Full
+ 100baseT/Half 100baseT/Full
+ 1000baseT/Full
+Advertised pause frame use: No
+Advertised auto-negotiation: Yes
+Link partner advertised link modes: Not reported
+Link partner advertised pause frame use: No
+Link partner advertised auto-negotiation: No
+Speed: 100Mb/s <--- Look Here! Should say 1000Mb/s!
+Duplex: Full
+Port: Twisted Pair
+PHYAD: 1
+Transceiver: internal
+Auto-negotiation: on
+MDI-X: Unknown
+Supports Wake-on: umbg
+Wake-on: g
+Current message level: 0x00000003 (3)
+Link detected: yes
+
+
+ In normal operation, the ICMP ping round trip time should be around 20ms, and the interface speed and duplex should read, "1000MB/s", and, "Full", respectively.
+
+
+
+ Resolution
+ After determining that the active ethernet adapter was at the incorrect speed, we used the ifenslave(8) command to make the standby interface
+ the active interface, which yielded an immediate improvement in MapReduce performance, and a 10 times improvement in network throughput:
+
+ On the next trip to the datacenter, we determined that the line speed issue was ultimately caused by a bad network cable, which was replaced.
+
+
+
+
+ Case Study #2 (Performance Research 2012)
+ Investigation results of a self-described "we're not sure what's wrong, but it seems slow" problem.
+ http://gbif.blogspot.com/2012/03/hbase-performance-evaluation-continued.html
+
+
+
+
+ Case Study #3 (Performance Research 2010))
+
+ Investigation results of general cluster performance from 2010. Although this research is on an older version of the codebase, this writeup
+ is still very useful in terms of approach.
+ http://hstack.org/hbase-performance-testing/
+
+
+
+
+ Case Study #4 (xcievers Config)
+ Case study of configuring xceivers, and diagnosing errors from mis-configurations.
+ http://www.larsgeorge.com/2012/03/hadoop-hbase-and-xceivers.html
+
+ See also .
+
+
+
+
diff --git a/src/docbkx/configuration.xml b/src/docbkx/configuration.xml
index 0daddbcfdbd..76d3ed02991 100644
--- a/src/docbkx/configuration.xml
+++ b/src/docbkx/configuration.xml
@@ -335,6 +335,8 @@ to ensure well-formedness of your document after an edit session.
java.io.IOException: No live nodes contain current block. Will get new
block locations from namenode and retry...
See Hadoop HDFS: Deceived by Xciever for an informative rant on xceivering.
+ See also
+
diff --git a/src/docbkx/performance.xml b/src/docbkx/performance.xml
index 2f7a00c563f..240052355d7 100644
--- a/src/docbkx/performance.xml
+++ b/src/docbkx/performance.xml
@@ -96,7 +96,7 @@
Network Interfaces
- Are all the network interfaces functioning correctly? Are you sure? See the Troubleshooting Case Study in .
+ Are all the network interfaces functioning correctly? Are you sure? See the Troubleshooting Case Study in .
@@ -433,7 +433,7 @@ Deferred log flush can be configured on tables via MapReduce - Input Splits
For MapReduce jobs that use HBase tables as a source, if there a pattern where the "slow" map tasks seem to
have the same Input Split (i.e., the RegionServer serving the data), see the
- Troubleshooting Case Study in .
+ Troubleshooting Case Study in .
@@ -539,4 +539,9 @@ htable.close();
because EC2 issues are practically a separate class of performance issues.
+
+ Case Studies
+ For Performance and Troubleshooting Case Studies, see .
+
+
diff --git a/src/docbkx/troubleshooting.xml b/src/docbkx/troubleshooting.xml
index 43dc98eccb9..79b5f6f5fab 100644
--- a/src/docbkx/troubleshooting.xml
+++ b/src/docbkx/troubleshooting.xml
@@ -1028,122 +1028,9 @@ in your Hadoop's lib directory. That should fix the above
- Case Study
- The issue described in this case study is somewhat exotic, but the thought process should
- provide a useful blueprint on diagnosing cluster issues.
- Scenario
- Following a scheduled reboot, one data node began exhibiting unusual behavior. Routine MapReduce
- jobs run against HBase tables which regularly completed in five or six minutes began taking 30 or 40 minutes
- to finish. These jobs were consistently found to be waiting on map and reduce tasks assigned to the troubled data node
- (e.g., the slow map tasks all had the same Input Split).
- The situation came to a head during a distributed copy, when the copy was severely prolonged by the lagging node.
-
-
- Hardware
- Datanodes:
-
- Two 12-core processors
- Six Enerprise SATA disks
- 24GB of RAM
- Two bonded gigabit NICs
-
-
- Network:
-
- 10 Gigabit top-of-rack switches
- 20 Gigabit bonded interconnects between racks.
-
-
-
- Hypotheses
- HBase "Hot Spot" Region
- We hypothesized that we were experiencing a familiar point of pain: a "hot spot" region in an HBase table,
- where uneven key-space distribution can funnel a huge number of requests to a single HBase region, bombarding the RegionServer
- process and cause slow response time. Examination of the HBase Master status page showed that the number of HBase requests to the
- troubled node was almost zero. Further, examination of the HBase logs showed that there were no region splits, compactions, or other region transitions
- in progress. This effectively ruled out a "hot spot" as the root cause of the observed slowness.
-
-
- HBase Region With Non-Local Data
- Our next hypothesis was that one of the MapReduce tasks was requesting data from HBase that was not local to the datanode, thus
- forcing HDFS to request data blocks from other servers over the network. Examination of the datanode logs showed that there were very
- few blocks being requested over the network, indicating that the HBase region was correctly assigned, and that the majority of the necessary
- data was located on the node. This ruled out the possibility of non-local data causing a slowdown.
-
-
- Excessive I/O Wait Due To Swapping Or An Over-Worked Or Failing Hard Disk
- After concluding that the Hadoop and HBase were not likely to be the culprits, we moved on to troubleshooting the datanode's hardware.
- Java, by design, will periodically scan its entire memory space to do garbage collection. If system memory is heavily overcommitted, the Linux
- kernel may enter a vicious cycle, using up all of its resources swapping Java heap back and forth from disk to RAM as Java tries to run garbage
- collection. Further, a failing hard disk will often retry reads and/or writes many times before giving up and returning an error. This can manifest
- as high iowait, as running processes wait for reads and writes to complete. Finally, a disk nearing the upper edge of its performance envelope will
- begin to cause iowait as it informs the kernel that it cannot accept any more data, and the kernel queues incoming data into the dirty write pool in memory.
- However, using vmstat(1) and free(1), we could see that no swap was being used, and the amount of disk IO was only a few kilobytes per second.
-
-
- Slowness Due To High Processor Usage
- Next, we checked to see whether the system was performing slowly simply due to very high computational load. top(1) showed that the system load
- was higher than normal, but vmstat(1) and mpstat(1) showed that the amount of processor being used for actual computation was low.
-
-
- Network Saturation (The Winner)
- Since neither the disks nor the processors were being utilized heavily, we moved on to the performance of the network interfaces. The datanode had two
- gigabit ethernet adapters, bonded to form an active-standby interface. ifconfig(8) showed some unusual anomalies, namely interface errors, overruns, framing errors.
- While not unheard of, these kinds of errors are exceedingly rare on modern hardware which is operating as it should:
-
-$ /sbin/ifconfig bond0
-bond0 Link encap:Ethernet HWaddr 00:00:00:00:00:00
-inet addr:10.x.x.x Bcast:10.x.x.255 Mask:255.255.255.0
-UP BROADCAST RUNNING MASTER MULTICAST MTU:1500 Metric:1
-RX packets:2990700159 errors:12 dropped:0 overruns:1 frame:6 <--- Look Here! Errors!
-TX packets:3443518196 errors:0 dropped:0 overruns:0 carrier:0
-collisions:0 txqueuelen:0
-RX bytes:2416328868676 (2.4 TB) TX bytes:3464991094001 (3.4 TB)
-
-
- These errors immediately lead us to suspect that one or more of the ethernet interfaces might have negotiated the wrong line speed. This was confirmed both by running an ICMP ping
- from an external host and observing round-trip-time in excess of 700ms, and by running ethtool(8) on the members of the bond interface and discovering that the active interface
- was operating at 100Mbs/, full duplex.
-
-$ sudo ethtool eth0
-Settings for eth0:
-Supported ports: [ TP ]
-Supported link modes: 10baseT/Half 10baseT/Full
- 100baseT/Half 100baseT/Full
- 1000baseT/Full
-Supports auto-negotiation: Yes
-Advertised link modes: 10baseT/Half 10baseT/Full
- 100baseT/Half 100baseT/Full
- 1000baseT/Full
-Advertised pause frame use: No
-Advertised auto-negotiation: Yes
-Link partner advertised link modes: Not reported
-Link partner advertised pause frame use: No
-Link partner advertised auto-negotiation: No
-Speed: 100Mb/s <--- Look Here! Should say 1000Mb/s!
-Duplex: Full
-Port: Twisted Pair
-PHYAD: 1
-Transceiver: internal
-Auto-negotiation: on
-MDI-X: Unknown
-Supports Wake-on: umbg
-Wake-on: g
-Current message level: 0x00000003 (3)
-Link detected: yes
-
-
- In normal operation, the ICMP ping round trip time should be around 20ms, and the interface speed and duplex should read, "1000MB/s", and, "Full", respectively.
-
-
-
- Resolution
- After determining that the active ethernet adapter was at the incorrect speed, we used the ifenslave(8) command to make the standby interface
- the active interface, which yielded an immediate improvement in MapReduce performance, and a 10 times improvement in network throughput:
-
- On the next trip to the datacenter, we determined that the line speed issue was ultimately caused by a bad network cable, which was replaced.
-
-
-
+ Case Studies
+ For Performance and Troubleshooting Case Studies, see .
+
+