This problem occurred when I used chipyard to compile Boom. Is this because of insufficient memory? I am running on a 1 core 2G cloud server.
/bin/bash: line 1: 9986 Killed java -Xmx8G -Xss8M
-XX:MaxPermSize=256M -jar /home/cuiyujie/workspace/Boom/chipyard/generators/rocket-chip/sbt-launch.jar
-Dsbt.sourcemode=true -Dsbt.workspace=/home/cuiyujie/workspace/Boom/chipyard/tools ";project utilities; runMain utilities.GenerateSimFiles -td
/home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig
-sim verilator"
/home/cuiyujie/workspace/Boom/chipyard/common.mk:86: recipe for target
'/home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/sim_files.f'
failed
make: *** [/home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/sim_files.f]
Error 137
When I adjusted the memory to 4G, this appeared.
Done elaborating. OpenJDK 64-Bit Server VM warning: INFO:
os::commit_memory(0x00000006dc3b7000, 97148928, 0) failed;
error='Cannot allocate memory' (errno=12)
There is insufficient memory for the Java Runtime Environment to continue.
Native memory allocation (mmap) failed to map 97148928 bytes for committing reserved memory.
An error report file with more information is saved as:
/home/cuiyujie/workspace/Boom/chipyard/hs_err_pid2876.log /home/cuiyujie/workspace/Boom/chipyard/common.mk:97: recipe for target
'generator_temp' failed make: *** [generator_temp] Error 1
Should I adjust to 8G memory, or through what command to increase the memory size that the process can use?
When I adjusted the memory to 16G, this appeared.
/bin/bash: line 1: 2642 Killed java -Xmx8G -Xss8M
-XX:MaxPermSize=256M -jar /home/cuiyujie/workspace/Boom/chipyard/generators/rocket-chip/sbt-launch.jar
-Dsbt.sourcemode=true -Dsbt.workspace=/home/cuiyujie/workspace/Boom/chipyard/tools ";project tapeout; runMain barstools.tapeout.transforms.GenerateTopAndHarness -o
/home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.top.v
-tho /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.harness.v
-i /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.fir
--syn-top ChipTop --harness-top TestHarness -faf /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.anno.json
-tsaof /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.top.anno.json
-tdf /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/firrtl_black_box_resource_files.top.f
-tsf /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.top.fir
-thaof /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.harness.anno.json
-hdf /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/firrtl_black_box_resource_files.harness.f
-thf /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.harness.fir
--infer-rw --repl-seq-mem -c:TestHarness:-o:/home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.top.mems.conf
-thconf /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.harness.mems.conf
-td /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig
-ll error" /home/cuiyujie/workspace/Boom/chipyard/common.mk:123: recipe for target 'firrtl_temp' failed make: *** [firrtl_temp] Error
137
Short answer : yes
Error 137 is thrown when your host runs out of memory.
"I am running on a 1 core 2G cloud server"
When you try to assign 8GB to the JVM, OOM-Killer says "no-no, f... no way", and kicks in sending a SIGKILL; This Killer is a proactive process that jumps into saving the system when its memory level goes too low, by killing the resource-abusive processes.
In this case, the abusive process (very abusive, indeed) is your java program, which is trying to allocate more than(*) 4 times the maximum available memory in your host.
Exit Codes With Special Meanings
[error code 137 --> kill -9] (SIGKILL)
You should either:
Assign at max ~1.2GB - 1.5GB to your process. (and keep your fingers crossed)
Change your host for something a little powerful/bigger if you do require that much memory for your process.
Check if you really require 8GB for that process.
Also note that the given params are error-prone: Xmx8G -Xss8M means a maximum of 8GB and a minimum of 8M for the heap. This should be closer, as Xmx8G - Xms4G
*As the free memory won't be 2GB either, but something in between 1.6-1.8 GB
Related
I run JMeter test for ActiveMQ using Linux build agent I've got java.lang.OutOfMemoryError: Java heap space. Detailed log:
at java.util.Arrays.copyOf(Arrays.java:3332)
at java.lang.AbstractStringBuilder.ensureCapacityInternal(AbstractStringBuilder.java:124) ~
at java.lang.AbstractStringBuilder.append(AbstractStringBuilder.java:448)
at java.lang.StringBuilder.append(StringBuilder.java:136
at org.apache.jmeter.protocol.jms.sampler.SubscriberSampler.extractContent(SubscriberSampler.java:282) ~[ApacheJMeter_jms.jar:5.3]
at org.apache.jmeter.protocol.jms.sampler.SubscriberSampler.sample(SubscriberSampler.java:186) ~[ApacheJMeter_jms.jar:5.3
at org.apache.jmeter.protocol.jms.sampler.BaseJMSSampler.sample(BaseJMSSampler.java:98) ~
at org.apache.jmeter.threads.JMeterThread.doSampling(JMeterThread.java:635) ~[ApacheJMeter_core.jar:5.4]
at org.apache.jmeter.threads.JMeterThread.executeSamplePackage(JMeterThread.java:558) ~[ApacheJMeter_core.jar:5.4]
at org.apache.jmeter.threads.JMeterThread.processSampler(JMeterThread.java:489) ~[ApacheJMeter_core.jar:5.4]
at org.apache.jmeter.threads.JMeterThread.run(JMeterThread.java:256) ~[ApacheJMeter_core.jar:5.4]
I've already allocated maximum HEAP memory (-Xmx8g), but it doesn't help. Yet the same test with the same configuration on Windows build agent passed without Out of memory error.
How can it be handled? Maybe some configuration should be done for Linux machine?
Are you sure your Heap setting gets applied on Linux?
You can check it my creating a simple test plan with single JSR223 Sampler using the following code:
println('Max heap size: ' + Runtime.getRuntime().maxMemory() / 1024 / 1024 + ' megabytes')
and when you run JMeter in command-line non-GUI mode you will see the current maximum JVM heap size printed:
In order to make the change permanent amend this line in jmeter startup script according to your requirements.
The issue was resolved after updating Java to 11 version on Linux machines.
I´m having repeated crashes in my Cloudera cluster HDFS Datanodes due to an OutOfMemoryError:
java.lang.OutOfMemoryError: Java heap space
Dumping heap to /tmp/hdfs_hdfs-DATANODE-e26e098f77ad7085a5dbf0d369107220_pid18551.hprof ...
Heap dump file created [2487730300 bytes in 16.574 secs]
#
# java.lang.OutOfMemoryError: Java heap space
# -XX:OnOutOfMemoryError="/usr/lib64/cmf/service/common/killparent.sh"
# Executing /bin/sh -c "/usr/lib64/cmf/service/common/killparent.sh"...
18551 TS 19 ? 00:25:37 java
Wed Aug 7 11:44:54 UTC 2019
JAVA_HOME=/usr/lib/jvm/java-openjdk
using /usr/lib/jvm/java-openjdk as JAVA_HOME
using 5 as CDH_VERSION
using /run/cloudera-scm-agent/process/3087-hdfs-DATANODE as CONF_DIR
using as SECURE_USER
using as SECURE_GROUP
CONF_DIR=/run/cloudera-scm-agent/process/3087-hdfs-DATANODE
CMF_CONF_DIR=/etc/cloudera-scm-agent
4194304
When analyzing the heap dump, the apparent biggest suspects are millions of instances of ScanInfo apparently quequed in the ExecutorService of the class org.apache.hadoop.hdfs.server.datanode.DirectoryScanner.
When I inspect the content of each ScanInfo runnable object, I don´t see anything weird:
Apart from this and a bit high block count in HDFS, I don´t get any other information apart from the different DataNodes crashing randomly in my cluster.
Any idea why these objects keep queueing up in the DirectoryScanner thread pool?
You can try once below command.
$ hadoop dfsadmin -finalizeUpgrade
The -finalizeUpgrade command removes the previous version of the NameNode’s and DataNodes’ storage directories.
We are running elasticsearch-1.5.1 cluster with 6 nodes, Recent days I am facing the java.lang.OutOfMemoryError PermGen space issue in the cluster, This affect the node and the same will get down. I am restarting the particular node to get live.
We try to figure out this issue by giving heavy load to the cluster but unfortunatlly can't able to reproduce. But some how we are getting the same issue again and again in production.
Here some of yml file configuration
index.recovery.initial_shards: 1
index.query.bool.max_clause_count: 8192
index.mapping.attachment.indexed_chars: 500000
index.merge.scheduler.max_thread_count: 1
cluster.routing.allocation.node_concurrent_recoveries: 15
indices.recovery.max_bytes_per_sec: 50mb
indices.recovery.concurrent_streams: 5
Memory configuration
ES_HEAP_SIZE=10g
ES_JAVA_OPTS="-server -Des.max-open-files=true"
MAX_OPEN_FILES=65535
MAX_MAP_COUNT=262144
Update Question with below configuration
I suspect on the merge.policy.max_merged_segment related to this issue. We have 22 index in my cluster. the merge.policy.max_merged_segment for the indices is given below
7 indices has 20gb
3 indices has 10gb
12 indices has 5gb
Update with process information
esuser xxxxx 1 28 Oct03 ? 1-02:20:40
/usr/java/default/bin/java -Xms10g -Xmx10g -Djava.awt.headless=true
-XX:+UseParNewGC -XX:+UseConcMarkSweepGC -XX:CMSInitiatingOccupancyFraction=75 -XX:+UseCMSInitiatingOccupancyOnly -XX:+HeapDumpOnOutOfMemoryError -XX:+DisableExplicitGC -Dfile.encoding=UTF-8 -server -Des.max-open-files=true -Delasticsearch -Des.pidfile=/var/es/elasticsearch.pid -Des.path.home=/usr/es/elasticsearch -cp :/usr/es/elasticsearch/lib/elasticsearch-1.5.1.jar:/usr/es/elasticsearch/lib/:/usr/es/elasticsearch/lib/sigar/
-Des.default.path.home=/usr/es/elasticsearch -Des.default.path.logs=/es/es_logs -Des.default.path.data=/es/es_data -Des.default.path.work=/es/es_work -Des.default.path.conf=/etc/elasticsearch org.elasticsearch.bootstrap.Elasticsearch
Below the stack trace i am getting from elasticsearch cluster while search. But event while index time also i am getting the same issue. As per my observation some search/ index operation increase the PermGen, if the upcoming operations try to use the PermGen space the issue comes.
[2015-10-03 06:45:05,262][WARN ][transport.netty ] [es_f2_01] Message not fully read (response) for [19353573] handler org.elasticsearch.search.action.SearchServiceTransportAction$6#21a25e37, error [true], resetting
[2015-10-03 06:45:05,262][DEBUG][action.search.type ] [es_f2_01] [product_index][4], node[GoUqK7csTpezN5_xoNWbeg], [R], s[INITIALIZING]: Failed to execute [org.elasticsearch.action.search.SearchRequest#5c2fe4c4] lastShard [true]
org.elasticsearch.transport.RemoteTransportException: Failed to deserialize exception response from stream
Caused by: org.elasticsearch.transport.TransportSerializationException: Failed to deserialize exception response from stream
at org.elasticsearch.transport.netty.MessageChannelHandler.handlerResponseError(MessageChannelHandler.java:176)
at org.elasticsearch.transport.netty.MessageChannelHandler.messageReceived(MessageChannelHandler.java:128)
at org.elasticsearch.common.netty.channel.SimpleChannelUpstreamHandler.handleUpstream(SimpleChannelUpstreamHandler.java:70)
at org.elasticsearch.common.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:564)
at org.elasticsearch.common.netty.channel.DefaultChannelPipeline$DefaultChannelHandlerContext.sendUpstream(DefaultChannelPipeline.java:791)
at org.elasticsearch.common.netty.channel.Channels.fireMessageReceived(Channels.java:296)
at org.elasticsearch.common.netty.handler.codec.frame.FrameDecoder.unfoldAndFireMessageReceived(FrameDecoder.java:462)
at org.elasticsearch.common.netty.handler.codec.frame.FrameDecoder.callDecode(FrameDecoder.java:443)
at org.elasticsearch.common.netty.handler.codec.frame.FrameDecoder.messageReceived(FrameDecoder.java:303)
at org.elasticsearch.common.netty.channel.SimpleChannelUpstreamHandler.handleUpstream(SimpleChannelUpstreamHandler.java:70)
at org.elasticsearch.common.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:564)
at org.elasticsearch.common.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:559)
at org.elasticsearch.common.netty.channel.Channels.fireMessageReceived(Channels.java:268)
at org.elasticsearch.common.netty.channel.Channels.fireMessageReceived(Channels.java:255)
at org.elasticsearch.common.netty.channel.socket.nio.NioWorker.read(NioWorker.java:88)
at org.elasticsearch.common.netty.channel.socket.nio.AbstractNioWorker.process(AbstractNioWorker.java:108)
at org.elasticsearch.common.netty.channel.socket.nio.AbstractNioSelector.run(AbstractNioSelector.java:337)
at org.elasticsearch.common.netty.channel.socket.nio.AbstractNioWorker.run(AbstractNioWorker.java:89)
at org.elasticsearch.common.netty.channel.socket.nio.NioWorker.run(NioWorker.java:178)
at org.elasticsearch.common.netty.util.ThreadRenamingRunnable.run(ThreadRenamingRunnable.java:108)
at org.elasticsearch.common.netty.util.internal.DeadLockProofWorker$1.run(DeadLockProofWorker.java:42)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603)
at java.lang.Thread.run(Thread.java:722)
Caused by: java.lang.OutOfMemoryError: PermGen space
Can any help me to solve this issue. Thanks
The best solution is to use a "Java 8" JVM.
While you could modify the amount of heap your Java 7 JVM is using (by setting -XX:MaxPermSize=... if you are using an Oracle JVM), if you just upgrade the JVM to version 8, then you don't even need to tune the permgen size.
This is because in JVM 8, the permgen size shares the heap in a non-partitioned way, meaning that you will only run out of permgen space when you run out of heap.
this is not a duplicate question, i see this, i want to run a java prograrm and have this error:
Exception in thread "main" java.lang.OutOfMemoryError: Java heap space
at edu.stanford.nlp.ie.crf.CRFLogConditionalObjectiveFunction.empty2D(CRFLogConditionalObjectiveFunction.java:892)
at edu.stanford.nlp.ie.crf.CRFLogConditionalObjectiveFunction.<init>(CRFLogConditionalObjectiveFunction.java:134)
at edu.stanford.nlp.ie.crf.CRFLogConditionalObjectiveFunction.<init>(CRFLogConditionalObjectiveFunction.java:117)
at edu.stanford.nlp.ie.crf.CRFClassifier.getObjectiveFunction(CRFClassifier.java:1792)
at edu.stanford.nlp.ie.crf.CRFClassifier.trainWeights(CRFClassifier.java:1798)
at edu.stanford.nlp.ie.crf.CRFClassifier.train(CRFClassifier.java:1713)
at edu.stanford.nlp.ie.AbstractSequenceClassifier.train(AbstractSequenceClassifier.java:763)
at edu.stanford.nlp.ie.AbstractSequenceClassifier.train(AbstractSequenceClassifier.java:751)
at edu.stanford.nlp.ie.crf.CRFClassifier.main(CRFClassifier.java:2917)
according this i try this:
java -Xms2000m -cp stanford-ner.jar edu.stanford.nlp.ie.crf.CRFClassifier -prop fa.prop
but the error not fix and i see error again! when i was set a value more than 2000m, my os crashed, or i get this output:
...
...
//stanford log
...
Time to convert docs to data/labels: 8.8 seconds
Killed
how i can fix it
edit:
and for this
[stanford-ner]$ java -Xms1G -Xmx50G -cp stanford-ner.jar edu.stanford.nlp.ie.crf.CRFClassifier -prop fa.prop
i have this error:
[1000][2000][3000][4000][5000][6000]OpenJDK 64-Bit Server VM warning: INFO: os::commit_memory(0x00007f04c7c00000, 1225785344, 0) failed; error='Cannot allocate memory' (errno=12)
#
# There is insufficient memory for the Java Runtime Environment to continue.
# Native memory allocation (malloc) failed to allocate 1225785344 bytes for committing reserved memory.
# An error report file with more information is saved as:
# /stanford-ner/hs_err_pid1536.log
Instead of trying with Xms option,
java -Xms2000m -cp stanford-ner.jar edu.stanford.nlp.ie.crf.CRFClassifier -prop fa.prop
try with Xmx as below,
java -Xmx2000m -cp stanford-ner.jar edu.stanford.nlp.ie.crf.CRFClassifier -prop fa.prop
Reference: Exception in thread "main" java.lang.OutOfMemoryError: Java heap space
Looking at the software's purpose it is likely that it is very memory-consuming, so it is reasonable to assume that 1GB of heap just isn't sufficient, so you'll have to further increase your heap-size.
The messages you get when you try imply that you are using
a 32-bit-OS or
a 32-bit-VM
which might both limit you to a maximum heap-size of about 1.5GB (at least on windows).
So make sure you use a 64bit-VM on a 64-bit-OS and then try again to increase the heap-size.
I've downloaded Version 1.0.0 of WSO2 Enterprise Mobility Manager
I followed the Prerequisites
and
the General Server Configurations
System Win 7 64bit 12GB RAM
JDK java version "1.7.0_51"
Java(TM) SE Runtime Environment (build 1.7.0_51-b13)
JAVA_HOME is set to JDK Directory
if I execute:
<PRODUCT_HOME>\bin>wso2server.bat --run
I get following error:
JAVA_HOME environment variable is set to C:\Program Files\Java\jdk1.7.0_51
CARBON_HOME environment variable is set to C:\inetpub\wwwroot\WSO2MO~1.0\bin\..
java.lang.OutOfMemoryError: Java heap space
Dumping heap to C:\inetpub\wwwroot\WSO2MO~1.0\bin\..\repository\logs\heap-dump.h
prof ...
Heap dump file created [1077051686 bytes in 5.148 secs]
java.lang.reflect.InvocationTargetException
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.
java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAcces
sorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.wso2.carbon.bootstrap.Bootstrap.loadClass(Bootstrap.java:63)
at org.wso2.carbon.bootstrap.Bootstrap.main(Bootstrap.java:45)
Caused by: java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:2367)
at java.lang.AbstractStringBuilder.expandCapacity(AbstractStringBuilder.
java:130)
at java.lang.AbstractStringBuilder.ensureCapacityInternal(AbstractString
Builder.java:114)
at java.lang.AbstractStringBuilder.append(AbstractStringBuilder.java:535
)
at java.lang.StringBuffer.append(StringBuffer.java:322)
at java.io.BufferedReader.readLine(BufferedReader.java:363)
at java.io.BufferedReader.readLine(BufferedReader.java:382)
at org.wso2.carbon.server.extensions.DropinsBundleDeployer.processBundle
sInfoFile(DropinsBundleDeployer.java:146)
at org.wso2.carbon.server.extensions.DropinsBundleDeployer.perform(Dropi
nsBundleDeployer.java:71)
at org.wso2.carbon.server.Main.invokeExtensions(Main.java:149)
at org.wso2.carbon.server.Main.main(Main.java:94)
... 6 more
I tried to raise heap size in wso2server.bat on line 161 up to -Xms4000m XmX8000mbut then I get an error java.lang.OutOfMemoryError: Requested array size exceeds VM limit
What can I do to get the Enterprise Mobility Server succesfully running?
I tried to raise heap size in wso2server.bat on line 161 up to
-Xms4000 XmX8000
You omitted the units - which defaults to kilobytes. Try:
-Xms4g -Xmx8g
You might also try running with -verbose:gc and visualize the data with a tool like HPjmeter. This will help you with sizing the heap appropriately.
Your -Xms and -Xmx options are way too low. This may be helpful. The number after those options is not in KB or MB, it's in just B... Your JVM won't even run at 8000B. Try increasing it to a reasonable number.
Edit: The prerequisites you linked states you need:
~ 512 MB heap size. This is generally sufficient to process typical SOAP messages but the requirements vary with larger message sizes and the number of messages processed concurrently.