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These variations are truly good examples that demonstrate that in resource-constrained situations you cannot predict the way your application is going to die so do not base your expectations on a specific sequence of actions to be completed. When using the ChipScope Core Inserter flow within the ISE Design Suite Project Navigator or Standalone, the Core Inserter freezes after going to ILA parameters page. I am trying to use Apache Spark to process my large (~230k entries) cassandra dataset, but I am constantly running into different kinds of errors. Not the answer you're looking for?Browse other questions tagged java cassandra apache-spark apache-spark-sql spark-cassandra-connector or ask your own question. Is it possible I am damaging my long-term employability by staying at a company with terrible structure? I was using Eclipse with JVM Monitor to determine reasonable text size limit and found significant memory leak. The reason for this is that you are running the for loop in the event dispatch thread (see Event Dispatch Thread).
If you are running a long task, then you should run it in a different thread, so that the user interface keeps responsive. I think the triggered events from setting the caret position are queued in your case and can only be processed, when the loop is finished (cause both are processed in event dispatch thread).

Not the answer you're looking for?Browse other questions tagged java swing memory-leaks jtextpane caret or ask your own question. Why were Civil War battle techniques so bloody, if the US had learned guerrilla fighting in the Revolutionary War? In many other programming languages, the developers need to manually allocate and free memory regions so that the freed memory can be reused. By default the JVM is configured to throw this error if it spends more than 98% of the total time doing GC and when after the GC less than 2% of the heap is recovered. For this you have an arsenal of different tools at your fingertips such as profilers and memory dump analyzers.
However, the large dataset was indexed from a binary file that occupied only 22 MB, and doing nodetool status, I can see that only ~115 MB data is stored in both of my cassandra nodes. For now, it works for an input of 230782 records, with a standard program taking ~5 minutes with 3 partitions, while an equivalent spark SQL program made 7 partitions and finished in under 8 seconds !
How the GC detects that a particular part of memory is explained in more details in the Garbage Collection Handbook, but you can trust the GC to do its job well.
This means that the little amount GC was able to clean will be quickly filled again, forcing GC to restart the cleaning process again.

But be prepared to invest a lot of time and be aware that such tools pose a significant overhead to your Java runtime, thus they are not suitable for production usage. I have a spark setup of 3 nodes with 1 master and 2 workers, and the 2 workers also have a cassandra cluster installed with data indexed with a replication factor of 2.
I have also tried to use Spark SQL on my dataset, but have got similar results with that too. It should be noted that I used loop with String.format() only to simulate real data, and optimization of this part is worthless. This forms a vicious cycle where the CPU is 100% busy with GC and no actual work can be done. Where am I going wrong with my setup, and what should I do to successfully process my dataset, for both a Transformation-Action program and a program that uses Spark SQL. End users of the application face extreme slowdowns – operations which normally complete in milliseconds take minutes to finish.

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