reaper | Leandro Facchinetti ’ s REAPER effects and scripts
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Leandro Facchinetti’s REAPER effects and scripts
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QUESTION
Was doing some internal testing about a clustering solution on top of infinispan/jgroups and noticed that the expired entries were never becoming eligible for GC, due to a reference on the expiration-reaper, while having more than 1 nodes in the cluster with expiration enabled / eviction disabled. Due to some system difficulties the below versions are being used :
- JDK 1.8
- Infinispan 9.4.20
- JGroups 4.0.21
In my example I am using a simple Java main scenario, placing a specific number of data, expecting them to expire after a specific time period. The expiration is indeed happening, as it can be confirmed both while accessing the expired entry and by the respective event listener(if its configured), by it looks that it is never getting removed from the available memory, even after an explicit GC or while getting close to an OOM error.
So the question is :
Is this really expected as default behavior, or I am missing a critical configuration as per the cluster replication / expiration / serialization ?
Example :
Cache Manager :
...ANSWER
Answered 2021-May-22 at 23:27As it seems noone else had the same issue or using primitive objects as cache entries, thus haven't noticed the issue. Upon replicating and fortunately traced the root cause, the below points are coming up :
- Always implement Serializable /
hashCode/equalsfor custom objects that are going to end been transmitted through a replicated/synchronized cache. - Never put primitive arrays, as the
hashcode/equalswould not be calculated - efficiently- - Dont enable eviction with remove strategy on replicated caches, as upon reaching the maximum limit, the entries are getting removed randomly - based on TinyLFU - and not based on the expired timer and never getting removed from the JVM heap.
QUESTION
I'm pretty new working on python and this is my first "big" project. This is what I have worked on for the day. I am trying to work on this project that randomly generates a name when you click on a category and press the generate button. It randomly generates one name but when I press the generate button again it doesn't display another name. That's what I'm trying to figure out. Also if anyone doesn't mind, how can I check a box and generate a name on that category.
Thank you very much
...ANSWER
Answered 2021-May-11 at 12:44Your name choices are more naturally organized as Radiobutton widgets.
QUESTION
I'm using Spark 3.1 in Databricks (Databricks Runtime 8) with a very large cluster (25 workers with 112 Gb of memory and 16 cores each) to replicate several SAP tables in an Azure Data Lake Storage (ADLS gen2). For doing this, a tool is writting the deltas of all these tables into an intermediate system (SQL Server) and then, if I have new data for a certain table, I execute a Databricks job to merge the new data with the existing data available in ADLS.
This process is working fine for most of the tables, but some of them (the biggest ones) take a lot of time to be merged (I merge the data using the PK of each table) and the biggest one has started failing since a week ago (When a big delta of the table was generated). Trace of the error that I can see in the job:
Py4JJavaError: An error occurred while calling o233.sql. : org.apache.spark.SparkException: Job aborted. at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:234) at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.$anonfun$writeFiles$5(TransactionalWriteEdge.scala:246) ... .. ............................................................................................................................................................................................................................................................................................................................................................................ Caused by: org.apache.spark.SparkException: Exception thrown in awaitResult: at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:428) at com.databricks.sql.transaction.tahoe.perf.DeltaOptimizedWriterExec.awaitShuffleMapStage$1(DeltaOptimizedWriterExec.scala:153) at com.databricks.sql.transaction.tahoe.perf.DeltaOptimizedWriterExec.getShuffleStats(DeltaOptimizedWriterExec.scala:158) at com.databricks.sql.transaction.tahoe.perf.DeltaOptimizedWriterExec.computeBins(DeltaOptimizedWriterExec.scala:106) at com.databricks.sql.transaction.tahoe.perf.DeltaOptimizedWriterExec.doExecute(DeltaOptimizedWriterExec.scala:174) at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:196) at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:240) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:165) at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:236) at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:192) at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:180) ... 141 more Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: ShuffleMapStage 68 (execute at DeltaOptimizedWriterExec.scala:97) has failed the maximum allowable number of times: 4. Most recent failure reason: org.apache.spark.shuffle.FetchFailedException: Connection from /XXX.XX.XX.XX:4048 closed at org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:769) at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:684) at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:69) at .................................................................................................................................................................................................................................................................................................................................... ... java.lang.Thread.run(Thread.java:748) Caused by: java.io.IOException: Connection from /XXX.XX.XX.XX:4048 closed at org.apache.spark.network.client.TransportResponseHandler.channelInactive(TransportResponseHandler.java:146) at org.apache.spark.network.server.TransportChannelHandler.channelInactive(TransportChannelHandler.java:117) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:262) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:248) at io.netty.channel.AbstractChannelHandlerContext.fireChannelInactive(AbstractChannelHandlerContext.java:241) at io.netty.channel.ChannelInboundHandlerAdapter.channelInactive(ChannelInboundHandlerAdapter.java:81) at io.netty.handler.timeout.IdleStateHandler.channelInactive(IdleStateHandler.java:277) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:262) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:248) at io.netty.channel.AbstractChannelHandlerContext.fireChannelInactive(AbstractChannelHandlerContext.java:241) at io.netty.channel.ChannelInboundHandlerAdapter.channelInactive(ChannelInboundHandlerAdapter.java:81) at org.apache.spark.network.util.TransportFrameDecoder.channelInactive(TransportFrameDecoder.java:225) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:262) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:248) at io.netty.channel.AbstractChannelHandlerContext.fireChannelInactive(AbstractChannelHandlerContext.java:241) at io.netty.channel.DefaultChannelPipeline$HeadContext.channelInactive(DefaultChannelPipeline.java:1405) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:262) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:248) at io.netty.channel.DefaultChannelPipeline.fireChannelInactive(DefaultChannelPipeline.java:901) at io.netty.channel.AbstractChannel$AbstractUnsafe$8.run(AbstractChannel.java:818) at io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:164) at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:472) at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:497) at io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989) at io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74) at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30) ... 1 more
As the error is non descriptive, I have taken a look to each executor log and I have seen following message:
21/04/07 09:11:24 ERROR OneForOneBlockFetcher: Failed while starting block fetches java.io.IOException: Connection from /XXX.XX.XX.XX:4048 closed
And in the executor that seems to be unable to connect, I see the following error message:
21/04/06 09:30:46 ERROR SparkThreadLocalCapturingRunnable: Exception in thread Task reaper-7 org.apache.spark.SparkException: Killing executor JVM because killed task 5912 could not be stopped within 60000 ms. at org.apache.spark.executor.Executor$TaskReaper.run(Executor.scala:1119) at org.apache.spark.util.threads.SparkThreadLocalCapturingRunnable.$anonfun$run$1(SparkThreadLocalForwardingThreadPoolExecutor.scala:104) at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23) at org.apache.spark.util.threads.SparkThreadLocalCapturingHelper.runWithCaptured(SparkThreadLocalForwardingThreadPoolExecutor.scala:68) at org.apache.spark.util.threads.SparkThreadLocalCapturingHelper.runWithCaptured$(SparkThreadLocalForwardingThreadPoolExecutor.scala:54) at org.apache.spark.util.threads.SparkThreadLocalCapturingRunnable.runWithCaptured(SparkThreadLocalForwardingThreadPoolExecutor.scala:101) at org.apache.spark.util.threads.SparkThreadLocalCapturingRunnable.run(SparkThreadLocalForwardingThreadPoolExecutor.scala:104) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(
I have tried increasing the default shuffle parallelism (From 200 to 1200 as It's suggested here Spark application kills executor) and it seems that the job is more time in execution, but it fails again.
I have tried to monitor the SparkUI meanwhile the job is in execution:
But as you can see, the problem is the same: Some stages are failing because an executor its unreachable because a task has failed more than X times.
The big delta that I mentioned above has more or less 4-5 billion rows and the big dump that I want to merge has, more or less, 100 million rows. The table is not partitioned (yet) so the process is very work-intensive. What is failing is the merge part, not the process to copy the data from SQL Server to ADLS, so the merge is being done once the data to be merge is already in Parquet format.
Any idea of what is happening or what can I do in order to finish this merge?
Thanks in advance.
...ANSWER
Answered 2021-Apr-12 at 07:56Finally, I reviewed the cluster and I changed the spark.sql.shuffle.partitions property to 1600 in the code of the job that I wanted to execute with this configuration (Instead than changing this directly on the cluster). In my cluster I have 400 cores so I chose a multiple (1600) of that number.
After that, the execution finished in two hours. I came to this conclusion because, in my logs and Spark UI I observed a lot of disk spilling so I thought that the partitions wasn't fitting in the worker nodes.
QUESTION
I ran this code for my app
...ANSWER
Answered 2021-Mar-25 at 14:39UPDATE
Thread names indicate whatever the person who wrote the code that created the thread decided. There is no simple answer to that question.
However, some names seem self-explanatory, e.g. the names listed in the formatted output below. Names like:
main- The main threadFinalizer- The thread responsible for executingfinalize()methods.- . . .
Other names are documented. E.g. the javadoc of new Thread() says:
Allocates a new
Threadobject. This constructor has the same effect asThread (null, null, gname), wheregnameis a newly generated name. Automatically generated names are of the form"Thread-"+n, wherenis an integer.
So Thread-7 would appear to be the thread created by the 8th call to new Thread(...) that didn't specify a name.
A thread name like pool-1-thread-1 would then also be an auto-generate name, for Thread #1 in Thread Pool #1.
To print the result of calling Thread.getAllStackTraces() in an easily readable format, use code like this:
QUESTION
I have been trying to make a simple menu where the user can enter a line that they want to add to the paragraph and then search the word(s) that they enter. However, in the case of searching the words (Case 3) if the word that they search is not in the first line it doesn't work (I get no errors) but my code works in a separate file with manual inputs.
Here is my class
...ANSWER
Answered 2021-Mar-15 at 21:05for(int j = 0; j <3 ; j++) {
paragraph[j] ="Hello my name is" ;
}
QUESTION
I'm searching for word(s) in a string array and if found I want to return their line. I have tried to divide the searched input in an array and then search it in the paragraph array line by line. Which does not really work.
...ANSWER
Answered 2021-Mar-15 at 16:23The way you declare paragraph causes the issue here is a working code:
QUESTION
This is my pom.xml
4.0.0 org.springframework.boot spring-boot-starter-parent 2.1.6.RELEASE com.dummy lattt 0.0.1-SNAPSHOT war lattt lattt
...ANSWER
Answered 2021-Feb-18 at 15:45"Could not find artifact com.amazonaws:aws-java-sdk-bom:pom:2.15.4 in central"
To address this POM issue, please refer to the AWS Spring BOOT example applications that are located in https://github.com/awsdocs/aws-doc-sdk-examples/tree/master/javav2/usecases.
They all work and use AWS SDK For Java Version 2. I have deployed every one of them to the Cloud by using Elastic BeanStalk. Furthermore, these Spring Boot example apps interact with different AWS services like DynamoDB, Amazon RDS, Amazon S3, Amazon SES, Amazon Rekognition, etc.
Creating the Amazon Relational Database Service item tracker
Creating an example AWS photo analyzer application using the AWS SDK for Java
Once you are successful getting the apps to work using V2, then you can build some tests
QUESTION
I have a problem about implementing recommendation system by using Euclidean Distance.
What I want to do is to list some close games with respect to search criteria by game title and genre.
Here is my project link : Link
After calling function, it throws an error shown below. How can I fix it?
Here is the error
...ANSWER
Answered 2021-Jan-03 at 16:00The issue is that you are using euclidean distance for comparing strings. Consider using Levenshtein distance, or something similar, which is designed for strings. NLTK has a function called edit distance that can do this or you can implement it on your own.
QUESTION
Like in the title, what is the "-Dall" option, what does it do exactly?
...ANSWER
Answered 2020-Dec-08 at 01:30-D controls debugging. -Dall = all debugging.
The reason why there is no documentation is because the output changes between versions. In other words: You should never rely on the the output from -Dall.
Instead of understanding that output your time is better spent on reading https://zenodo.org/record/1146014 and https://www.gnu.org/software/parallel/parallel_design.html
QUESTION
I've only updated my application's gems and moved to Rails 6.1.0.rc1 and am now unable to run puma. I see a number of messages that say [7XXXX] Early termination of worker.
I can replicate this locally by running bundle exec puma -p 3000 -e production but I do not see any other output in log/production.log or any of the other environments' logs.
At this point besides waiting for a new Rails rc I'm not sure how I can find the root of the issue. There is also no problem if I run bundle exec puma -C config/puma.rb -p 3000 or bundle exec rails s.
In Gemfile
ANSWER
Answered 2020-Nov-09 at 21:22pumactl and having a control-url helped but a friend of mine suggested the best idea that I only wish was more obvious,
are you throwing the error on a different server?
I ran gem install thin and RAILS_ENV=production thin start finally showed me the error I was looking for!
As it turns out, I should not have been using non-public methods like add_template_helper as ActionMailer::Base may not always get all the methods of ActionController::Base. I didn't see this error in development because Rails does not eagerly load all of your classes.
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