how to resolve java heap space issue

How to fix java.lang.OutOfMemoryError: Java heap space

Nov 4, 2014

If you get an OutOfMemoryError with the message “Java heap space” (not to be confused with message “ PermGen space ”), it simply means the JVM ran out of memory. When it occurs, you basically have 2 options:

Solution 1. Allow the JVM to use more memory

With the -Xmx JVM argument, you can set the heap size. For instance, you can allow the JVM to use 4 GB (4096 MB) of memory with the following command:

Solution 2. Improve or fix the application to reduce memory usage

In many cases, like in the case of a memory leak, that second option is the only good solution. A memory leak happens when the application creates more and more objects and never releases them. The garbage collector cannot collect those objects and the application will eventually run out of memory. At this point, the JVM will throw an OOM ( OutOfMemoryError ).

A memory leak can be very latent. For instance, the application might behave flawlessly during development and QA. However, it suddenly throws a OOM after several days in production at customer site. To solve that issue, you first need to find the root cause of it. The root cause can be very hard to find in development if the problem cannot be reproduced. Follow those steps to find the root cause of the OOM:

Step 1. Generate a heap dump on OutOfMemoryError

Start the application with the VM argument -XX:+HeapDumpOnOutOfMemoryError . This will tell the JVM to produce a heap dump when a OOM occurs:

Step 2. Reproduce the problem

Well, if you cannot reproduce the problem in dev, you may have to use the production environment. When you reproduce the problem and the application throws an OOM, it will generate a heap dump file.

Step 3. Investigate the issue using the heap dump file

Use VisualVM to read the heap dump file and diagnose the issue. VisualVM is a program located in JDK_HOME/bin/jvisualvm . The heap dump file has all information about the memory usage of the application. It allows you to navigate the heap and see which objects use the most memory and what references prevent the garbage collector from reclaiming the memory. Here is a screenshot of VisualVM with a heap dump loaded:

Heap Dump in VisualVM

This will give you very strong hints and you will (hopefully) be able to find the root cause of the problem. The problem could be a cache that grows indefinitely, a list that keeps collecting business-specific data in memory, a huge request that tries to load almost all data from database in memory, etc.

Once you know the root cause of the problem, you can elaborate solutions to fix it. In case of a cache that grows indefinitely, a good solution could be to set a reasonable limit to that cache. In case of a query that tries to load almost all data from database in memory, you may have to change the way you manipulate data; you could even have to change the behavior of some functionalities of the application.

Manually triggering heap dump

If you do not want to wait for an OOM or if you just want to see what is in memory now, you can manually generate heap dump. Here 2 options to manually trigger a heap dump.

Option 1. Use VisualVM

Open VisualVM ( JDK_HOME/bin/jvisualvm ), right-click on the process on the left pane and select Heap Dump. That’s it.

Option 2. Use command line tools

If you do not have a graphical environment and can’t use vnc ( VisualVM needs a graphical environment), use jps and jmap to generate the heap dump file. Those programs are also located in JDK_HOME/bin/ .

Finally copy the heap dump file (heap.bin) to your workstation and use VisualVM to read the heap dump: File -> Load…

Alternatively, you can also use jhat to read heap dump files.

Solution 3 (bonus). Call me

You can also contact my application development company and I can personally help you with those kind of issues 🙂

Author: Jonathan Demers

How to Resolve the Issue java.lang.OutOfMemoryError: Java Heap Space

We are running 3 instances of ODK and 2 more Java applications on a single server. If we try to load all these applications simultaneously, some will not load and some will be slow. When we check tomcat's log file, Catalina. out, it says, java. lang.OutOfMemoryError: Java heap space. The cause of this is explained below,

Normally java applications are allowed to use only limited memory and java memory is separated into two different regions. These regions are called Heap space and Permgen (for Permanent Generation). The size of those regions is set during the Java Virtual Machine (JVM) launch and can be customized by specifying JVM parameters -Xmx and -XX: MaxPermSize. The java. lang.OutOfMemoryError: Java heap space error occurs when it attempts to add more data into the heap space area, but there is not enough room for it.

The solution to fix this problem is to increase the heap space(Default value maybe 128 MB). We can customize the heap space by specifying the JVM parameters -Xmx and -XX: MaxPermSize.

To achieve this, please do the following,

Hope this helps! Please feel free to get in touch with us for further queries.

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Java heap related issues can cause severe damage to your application that will directly result in poor end user experience . Care must be taken to tune the Heap related parameters that suit your application. Out of the box default parameters are not enough.

Quick overview:

Java Heap is the memory used by your application to create and store objects. You define the maximum memory that can be for the Heap by specifying ‘-Xmx<size>’ java command line option (Example: ‘ -Xmx1024m ‘, where m stands for Mega bytes). As your application runs, it will gradually fill up Heap. JVM periodically runs a process called ‘ Garbage collection’ (GC) which will scan the heap and clear objects that are no longer referenced by your application.One cannot request Garbage Collection on demand. Only JVM can decide when to run GC.

Let me walk you through four of the most common Java Heap related issues and how to fix them.

1. ‘ OutOfMemory’ Error due to insufficient Heap

This is when JVM runs out of Heap and GC is unable to reclaim memory to meet the demand of the application. This error simply means that the Heap is filled with objects that are being used/referenced by your application.

It is possible that you indeed are using all the objects i.e there is real demand for memory. For example, if you are doing heavy weight activities like processing images/video or crunching big numbers.

How to identify ?

When you plot the heap usage graph (how to do this? Answer at the end of this article), you will most probably see a sudden spike in memory utilization , indicating a heavy weight transaction has just started. This will be in contrast to a ‘gradual increase in heap.

You could try increasing the Heap size to see if you can live through the heavy weight transaction. Sometimes this is enough. But some times, the code needs to be revisited to see why the demand is high in first place . May be you are trying to pull millions of records from DB and process them at once. May be you are processing something unnecessarily.

2. Poor application response time due to long Garbage Collection Pauses

As mentioned earlier GC is responsible for scanning the heap and clearing unused objects so that the memory can be reclaimed. This can be a resource intensive process especially when the heap is big and it is filled to the brink. In most cases, when GC is running, the entire JVM is paused. When GC takes a long time to complete the JVM pause time also becomes long resulting in very poor end user experience. Ideally each GC pause should be less than 500ms depending upon how often the GC runs.

When you plot the graph for GC Time (How to do this ? Answer at the end of this article), you will see longer duration (several seconds). You will also hear from your customers about poor performance. In some cases, the CPU utilization of the Server can go up significantly as well.

Tuning can help . Make sure you have ‘generational’ heap configured . With generational heap, the heap has a special area called ‘nursery’ or ‘new generation’ that is used for short lived objects. The idea is GC is will be quicker in ‘new generation’ since the entire heap does not have to be scanned. The heap also has a ‘tenured’ or ‘old generation’ ara where long living objects are stored. A minor GC works on new generation and a Major GC (Full GC) works on the entire heap. This issue can also be code related so you need to analyze the code in parallel to tuning the heap. Some JVMs like IBM have an option to specify a GC policy such as ‘optgcpause’ which optimizes GC for smaller pause time.

3. OutofMemory Error due to Memory leak

Memory leak means the application is allocating memory and holding on to them unnecessarily. What this means is, after certain period, the heap will be filled with objects are being used by the application and GC will NOT be able to reclaim those. This results in the gory ‘OutOfMemory’ error.

When you plot the heap graph, you would see a ‘staircase’ pattern, indicating a gradual leak (rather than a sudden spike). You will also face ‘OutOfMemory’ errors

Memory leak is most probably code issue. This can also happen due to a library you are using that is outside of your code. Profiling your application using tools like Jprobe will shed light.

4. Heap fragmentation

Heap gets fragmented when small and large objects are allocated in a mixed fashion that have various lifetimes. To some extent, you cannot avoid fragmentation – over time, heap will get fragmented. But there is couple of crucial things to consider.

a. When heap is fragmented, GC will try to compact the heap which can result in a longer GC pause time for a heavily fragmented heap

b. Heap fragmentation becomes an issue ONLY when your application requires to allocate memory for a large object (which will need contiguous blocks of memory).

You will see poor application response times, longer GC pauses and in some case ‘OutOfMemory’ errors.

Tuning can help. This is when tuning becomes extremely vendor specific (HP,IBM,Hotspot etc). You will have to check your JVM’s options (see if there is support for -XXcompactRatio). Also note that newer versions of JVMs are much efficient in handling the fragmentation as they dynamically compact the heap. So, you may never really run into this issue if you use newer releases of your JVM.

Now, How to monitor heap and GC ?

There are several options:

1. Use -verbose:gc to get verbose GC logs. It can be life saver. There are tools to analyze the verbose GC logs

2. Use JDK tools such as jconsole,visualvm and jstat.

3. Procure a commercial APM (Application Performance Management) tool that will not only monitor the heap but can alert you when things are about to get bad. APM can also help in identifying memory leaks.

You may want to take a look at my other article http://karunsubramanian.com/java/5-not-so-easy-ways-to-monitor-the-heap-usage-of-your-java-application/

Final note: The use of Heap dumps:

Heap dump can be an invaluable tool in troubleshooting memory related issues. A heap dump is a copy of the entire heap when the heap dump was taken. We can readily identify the objects that are filling up te memory by analyzing the heap dump (You can use Eclipse Memory analyzer)

There you have it. 4 most common heap related issues and how to fix them.

LEARN WITH PASSION

very useful article. thanks

Very good Information.

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Spark java.lang.OutOfMemoryError: Java heap space

My cluster: 1 master, 11 slaves, each node has 6 GB memory.

Here is the problem:

First , I read some data (2.19 GB) from HDFS to RDD:

Second , do something on this RDD:

Last , output to HDFS:

When I run my program it shows:

There are too many tasks?

PS : Every thing is ok when the input data is about 225 MB.

How can I solve this problem?

14 Answers 14

I have a few suggestions:

http://spark.apache.org/docs/1.2.1/configuration.html

EDIT : (So I can google myself easier) The following is also indicative of this problem:

To add a use case to this that is often not discussed, I will pose a solution when submitting a Spark application via spark-submit in local mode.

According to the gitbook Mastering Apache Spark by Jacek Laskowski :

You can run Spark in local mode. In this non-distributed single-JVM deployment mode, Spark spawns all the execution components - driver, executor, backend, and master - in the same JVM. This is the only mode where a driver is used for execution.

Thus, if you are experiencing OOM errors with the heap , it suffices to adjust the driver-memory rather than the executor-memory .

Here is an example:

You should configure offHeap memory settings as shown below:

Give the driver memory and executor memory as per your machines RAM availability. You can increase the offHeap size if you are still facing the OutofMemory issue .

You should increase the driver memory. In your $SPARK_HOME/conf folder you should find the file spark-defaults.conf , edit and set the spark.driver.memory 4000m depending on the memory on your master, I think. This is what fixed the issue for me and everything runs smoothly

How much percentage of mem to be alloted, in stand alone – Yashwanth Kambala Oct 4, 2019 at 13:15

Have a look at the start up scripts a Java heap size is set there, it looks like you're not setting this before running Spark worker.

You can find the documentation to deploy scripts here .

I suffered from this issue a lot when using dynamic resource allocation. I had thought it would utilize my cluster resources to best fit the application.

But the truth is the dynamic resource allocation doesn't set the driver memory and keeps it to its default value, which is 1G.

I resolved this issue by setting spark.driver.memory to a number that suits my driver's memory (for 32GB ram I set it to 18G).

You can set it using spark submit command as follows:

Very important note, this property will not be taken into consideration if you set it from code, according to Spark Documentation - Dynamically Loading Spark Properties :

Spark properties mainly can be divided into two kinds: one is related to deploy, like “spark.driver.memory”, “spark.executor.instances”, this kind of properties may not be affected when setting programmatically through SparkConf in runtime, or the behavior is depending on which cluster manager and deploy mode you choose, so it would be suggested to set through configuration file or spark-submit command line options; another is mainly related to Spark runtime control, like “spark.task.maxFailures”, this kind of properties can be set in either way.

2 You should use --conf spark.driver.memory=18g – merenptah Mar 29, 2019 at 7:30

Broadly speaking, spark Executor JVM memory can be divided into two parts. Spark memory and User memory. This is controlled by property spark.memory.fraction - the value is between 0 and 1. When working with images or doing memory intensive processing in spark applications, consider decreasing the spark.memory.fraction . This will make more memory available to your application work. Spark can spill, so it will still work with less memory share.

The second part of the problem is division of work. If possible, partition your data into smaller chunks. Smaller data possibly needs less memory. But if that is not possible, you are sacrifice compute for memory. Typically a single executor will be running multiple cores. Total memory of executors must be enough to handle memory requirements of all concurrent tasks. If increasing executor memory is not a option, you can decrease the cores per executor so that each task gets more memory to work with. Test with 1 core executors which have largest possible memory you can give and then keep increasing cores until you find the best core count.

The location to set the memory heap size (at least in spark-1.0.0) is in conf/spark-env. The relevant variables are SPARK_EXECUTOR_MEMORY & SPARK_DRIVER_MEMORY . More docs are in the deployment guide

Also, don't forget to copy the configuration file to all the slave nodes.

Did you dump your master gc log? So I met similar issue and I found SPARK_DRIVER_MEMORY only set the Xmx heap. The initial heap size remains 1G and the heap size never scale up to the Xmx heap.

Passing "--conf "spark.driver.extraJavaOptions=-Xms20g" resolves my issue.

ps aux | grep java and the you'll see the follow log:=

24501 30.7 1.7 41782944 2318184 pts/0 Sl+ 18:49 0:33 /usr/ java /latest/bin/ java -cp /opt/spark/conf/:/opt/spark/jars/* -Xmx30g -Xms20g

I have few suggession for the above mentioned error.

● Check executor memory assigned as an executor might have to deal with partitions requiring more memory than what is assigned.

● Try to see if more shuffles are live as shuffles are expensive operations since they involve disk I/O, data serialization, and network I/O

● Use Broadcast Joins

● Avoid using groupByKeys and try to replace with ReduceByKey

● Avoid using huge Java Objects wherever shuffling happens

From my understanding of the code provided above, it loads the file and does map operation and saves it back. There is no operation that requires shuffle. Also, there is no operation that requires data to be brought to the driver hence tuning anything related to shuffle or driver may have no impact. The driver does have issues when there are too many tasks but this was only till spark 2.0.2 version. There can be two things which are going wrong.

Simple if you are using a script or juyter notebook then set only config path when you start build a spark session...

Worked like magic for me! – Merin Nakarmi Nov 17, 2022 at 19:19

heap space errors generally occur due to either bringing too much data back to the driver or the executor. In your code it does not seem like you are bringing anything back to the driver, but instead you maybe overloading the executors that are mapping an input record/row to another using the threeDReconstruction() method. I am not sure what is in the method definition but that is definitely causing this overloading of the executor. Now you have 2 options,

I would advise being careful with the increase and use only as much as you need. Each job is unique in terms of its memory requirements, so I would advise empirically trying different values increasing every time by a power of 2 (256M,512M,1G .. and so on)

You will arrive at a value for the executor memory that will work. Try re-running the job with this value 3 or 5 times before settling for this configuration.

Setting these exact configurations helped resolving the issue.

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How to resolve OutOfMemoryError: Java heap space error.

Article id: 44142, updated on:, issue/introduction.

We have seen below error message in the IM console and server.log. What should we do?

java.lang.OutOfMemoryError: Java heap space

Environment

The error indicates that Java ran out of memory to allocate to the application resulting in anything from minor issues such as that activity having to wait to complete, to complete system outages.

Additional Information

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Inštitut za raziskovanje zvočnih umetnosti

how to resolve java heap space issue

Java Heap Space, How To Fix It? Example

Eclipse: Java heap space, How to fix it? Example

With this article, we’ll look at some examples of how to address the Eclipse: Java heap space, How to fix it? Example problem .

The Eclipse: Java heap space, How to fix it? Example was solved using a number of scenarios, as we have seen.

Table of Contents

How do I fix Java heap space error?

Fixing Java. lang. outofmemory Error in Java

How do I increase the heap size available to Eclipse?

Since Eclipse is a Java program, you can increase the heap size of Eclipse by using JVM memory options -Xms and -Xmx. There are two ways to provide JVM options to eclipse either updating the Eclipse shortcut or adding -vmargs on eclipse. ini file.

How do I resolve heap size?

There are several ways to eliminate a heap memory issue: Increase the maximum amount of heap available to the VM using the -Xmx VM argument. Use partitioning to distribute the data over additional machines. Overflow or expire the region data to reduce the heap memory footprint of the regions.12-Jun-2018

How do I fix out of memory in Eclipse?

Tuning Eclipse Performance and Avoiding OutOfMemory Exceptions

How do I free up JVM memory?

There is no way to force JVM to free up the memory, System. gc() is just a hint. It’s up to GC to manage the memory (do note there are various types of memory e.g. heap, meta space, off-heap).19-Jan-2019

How do I fix heap size limit exceeding?

If you find the heap size error, it is always caused by SOQL statement returning more than 30,000 records or more OR collection objects holding too many records in memory. To fix it, remove the SOQL statement and put a “where condition” to return a limited records (1 to 5) and fine tune any collection object.20-Dec-2016

How do I see heap memory in Eclipse?

Goto Window > Preferences > General and enable Show heap status and click OK. In the status bar of eclipse (bottom of the screen) a new UI element will appear. We can see 3 things: The amount of used memory by the application (including garbage that has not been collected), in the example 111MB.11-Nov-2011

What is the max heap size for 64 bit JVM?

For 64 bit platforms and Java stacks in general, the recommended Maximum Heap range for WebSphere Application Server, would be between (4096M – 8192M) or (4G – 8G).

What happens if heap is full?

When the heap becomes full, garbage is collected. During the garbage collection objects that are no longer used are cleared, thus making space for new objects.

What causes Java heap space error?

Usually, this error is thrown when there is insufficient space to allocate an object in the Java heap. In this case, The garbage collector cannot make space available to accommodate a new object, and the heap cannot be expanded further.

Read more here: Source link

Learn & Share

Resolve the “java.lang.outofmemoryerror: java heap space” issue in spark and hive(tez and mr).

how to resolve java heap space issue

OOM in the Driver process

To resolve the issue

OOM in the Executor process

We can tune the memory provided to the Executor and the number of executors to distribute the load

In HIVE (Tez or MR)

Example ERROR message

Also, consider tuning the code and data size for better performance.

Good luck with your Learning !!

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java.lang.OutOfMemoryError: Java heap space #2

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Error: 'java heap space', how to fix it.

How do I resolve the "java.lang.OutOfMemoryError: Java heap space" error in AWS Glue?

Last updated: 2022-02-07

My AWS Glue job fails with "Command failed with exit code 1" and Amazon CloudWatch Logs shows the "java.lang.OutOfMemoryError: Java heap space" error.

Short description

The "java.lang.OutOfMemoryError: Java heap space" error indicates that a driver or executor process is running out of memory. To determine whether a driver or an executor causes the OOM, see Debugging OOM exceptions and job abnormalities . The following resolution is for driver OOM exceptions only.

Driver OOM exceptions commonly happen when an Apache Spark job reads a large number of small files from Amazon Simple Storage Service (Amazon S3). Resolve driver OOM exceptions with DynamicFrames using one or more of the following methods.

When you activate the grouping feature, tasks process multiple files instead of individual files. For more information, see Fix the processing of multiple files using grouping .

Activate useS3ListImplementation

AWS Glue creates a file index in driver memory lists when it lists files. When you set useS3ListImplementation to True , as shown in the following example, AWS Glue doesn't cache the list of files in memory all at once. Instead, AWS Glue caches the list in batches. This means that the driver is less likely to run out of memory.

Here's an example of how to activate useS3ListImplementation with from_catalog :

Here's an example of how to activate useS3ListImplementation with from_options :

The useS3ListImplementation feature is an implementation of the Amazon S3 ListKeys operation , which splits large results sets into multiple responses. It's a best practice to use useS3ListImplementation with job bookmarks.

Additional troubleshooting

If grouping and useS3ListImplementation don't resolve driver OOM exceptions, try the following:

Related information

Optimize memory management in AWS Glue

Reading input files in larger groups

Best practices for successfully managing memory for Apache Spark applications on Amazon EMR

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How to: fix java heap space error that may occur during the import of huge repository in linux os.

This situation and stack trace may occur during the import of a repository that contains a big number of objects.

To fix this problem, the Java Heap Space value should be increased up to the value that

could allow you to finish the import operation without any memory related errors.

navigate to the configuration files that contains this adjustment:

buildomatic\js-import.sh

buildomatic\bin\js-import-export.sh

buildomatic\bin\import-export.xml

set the same value for the -Xmx parameter in the 3 configuration files

that are mentioned above

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Sitecore Diaries

Learn, explore and enjoy sitecoring, how to resolve solr heap size issue.

We recently started facing heap size issue on one of our SOLR instance.

I thought it was easy fix by just adding more memory but it wasn’t as forward as I thought. Before you jump to the solution I will share a good link which will explain you the cause of it in the first place.

https://sitecore.stackexchange.com/questions/622/how-much-memory-does-the-jvm-for-solr-need

This can be fixed by updating the memory value double of what is currently present in your SOLR instance (default is 512 MB)

Tip: It wasn’t allowing me to use 1024m and the service was throwing error, I used 1000m and it worked.

If the above steps doesn’t work then you can update the values in solr.cmd file.

The links that I referred while troubleshooting are:

Thank you.. Keep Learning.. Keep Sitecoring.. 🙂

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COMMENTS

How to fix java.lang.OutOfMemoryError: Java heap space
To solve that issue, you first need to find the root cause of it. The root cause can be very hard to find in development if the problem cannot be reproduced. Follow those steps to find the root cause of the OOM: Step 1. Generate a heap dump on OutOfMemoryError Start the application with the VM argument -XX:+HeapDumpOnOutOfMemoryError.
In How many ways we can Resolve Heap Space issue in java?
*obviously the Oracle java site should be your first point of call. 1) I don't think you can adjust the heap space dynamically during runtime. So setting it the start is a must. 2) Depends on if you are running a 32/64bit OS, and how much RAM you have on the PC 3) See link above and Oracle's own docs, it is too large to describe :)
How to Resolve the Issue java.lang.OutOfMemoryError: Java Heap Space
The solution to fix this problem is to increase the heap space (Default value maybe 128 MB). We can customize the heap space by specifying the JVM parameters -Xmx and -XX: MaxPermSize. To achieve this, please do the following, Edit the catalina.sh file loacted in the bin directory of tomcat (/usr/share/tomcat7/bin).
java.lang.OutOfMemoryError: Java heap space
If you want to increase your heap space, you can use java -Xms<initial heap size> -Xmx<maximum heap size> on the command line. By default, the values are based on the JRE version and system configuration. You can find out more about the VM options on the Java website.
How to fix Java heap space error in Talend?
Add the -Xmx parameter to specify the maximum heap size. The default value depends on various factors like the JVM release/vendor, the actual memory of the machine, etc... In your situation, the java.lang.OutOfMemoryError: Java heap space reveals that the default value is not enough for this job so you need to override it.
Top 4 Java Heap related issues and how to fix them
Let me walk you through four of the most common Java Heap related issues and how to fix them. 1. ' OutOfMemory' Error due to insufficient Heap This is when JVM runs out of Heap and GC is unable to reclaim memory to meet the demand of the application.
java
It is important to perform a proper diagnostic first: Enable verbose:gc. This will allow you to understand the memory growing pattern over time. Generate and analyze a JVM Heap Dump. This will allow you to understand your application memory footprint and pinpoint the source of the memory leak (s).
out of memory
Make sure you're using as much memory as possible by checking the UI (it will say how much mem you're using) Try using more partitions, you should have 2 - 4 per CPU. IME increasing the number of partitions is often the easiest way to make a program more stable (and often faster).
How to Fix JavaScript Heap Out of Memory Error
To set a different value, multiply the amount you require in GB by 1024 (the variable value needs to be in MB). Click on OK to save your changes, then click Apply and finally click OK once more ...
How to resolve out of memory error Java heap space
Increase heap size first. Use correct memory parameters [1] either with jar or <crx-quickstart folder>/bin/start script when starting AEM instance. Check your servlet/custom code for any possible memory leaks. Thanks, Wasil [1] Increase java heap size - /home/edivad 18.0K 16 1 Like Translate Reply Qamar_khan Level 3 02-01-2019 05:41 PST
How to resolve OutOfMemoryError: Java heap space error.
java.lang.OutOfMemoryError: Java heap space Environment CA Identity Manager Cause The error indicates that Java ran out of memory to allocate to the application resulting in anything from minor issues such as that activity having to wait to complete, to complete system outages. Resolution
Java Heap Space, How To Fix It? Example
How do I resolve heap size? There are several ways to eliminate a heap memory issue: Increase the maximum amount of heap available to the VM using the -Xmx VM argument. Use partitioning to distribute the data over additional machines. Overflow or expire the region data to reduce the heap memory footprint of the regions.12-Jun-2018
Resolve the "java.lang.OutOfMemoryError: Java heap space" issue in
Executors are the slave Java process, Where the actual task runs, As we know spark is memory intense framework, it is essential to provide the memory needed for processing else you will be seeing OOM. To resolve the issue. We can tune the memory provided to the Executor and the number of executors to distribute the load
java.lang.OutOfMemoryError: Java heap space · Issue #2 · nackily/imglib
Exception in thread "main" java.lang.OutOfMemoryError: Java heap space at java.awt.image.DataBufferInt.(DataBufferInt.java:75) at java.awt.image ...
Java.lang.outofmemoryerror: java heap space
Solution 1: The easiest solution to remove such error is to increase the memory size of the JVM heap space. To increase the size of the heap space, use "-Xmx" java options to solve the out-of-memory error. This configuration will provide 1024 heap space to the application.
ERROR: 'Java heap space', how to fix it
xmlResult = new StreamResult (new FileOutputStream ("C:/temp/outFilename")); try { // on this line of code , i get the heap size error. xsltengine.transform (xmlSource, xmlResult); }catch (Exception e) { System.out.println ("IN TRANSER HEAP prblem"); e.printStackTrace (); } logger.info ("XML TO WML TRANSFORMATION IS COMPLETED.");
Resolve "OutOfMemoryError" Hive Java heap space exceptions on Amazon
How do I resolve "OutOfMemoryError" Hive Java heap space exceptions on Amazon EMR that occur when Hive outputs the query results? ... the Hive metastore, or the client side. To resolve this issue, increase the maximum memory allocation for the JVM or increase HADOOP_HEAPSIZE. ... # # java.lang.OutOfMemoryError: Java heap space # -XX ...
Resolve the "java.lang.OutOfMemoryError: Java heap space" error in AWS Glue
AWS Glue creates a file index in driver memory lists when it lists files. When you set useS3ListImplementation to True, as shown in the following example, AWS Glue doesn't cache the list of files in memory all at once.Instead, AWS Glue caches the list in batches. This means that the driver is less likely to run out of memory.
How to: fix Java Heap Space error that may occur during the import of
Solution: To fix this problem, the Java Heap Space value should be increased up to the value that could allow you to finish the import operation without any memory related errors. To do this: navigate to the configuration files that contains this adjustment: buildomatic\js-import.sh buildomatic\bin\js-import-export.sh
How to resolve SOLR Heap size issue?
We recently started facing heap size issue on one of our SOLR instance. Error: Caused by: java.lang.OutOfMemoryError: Java heap space. I thought it was easy fix by just adding more memory but it wasn't as forward as I thought. Before you jump to the solution I will share a good link which will explain you the cause of it in the first place.