Memory fragmentation? Quiet common with in-memory systems. > On 08 Jul 2016, at 08:56, aasish.kumar <aasish.ku...@avekshaa.com> wrote: > > Hello everyone: > > I have been facing a problem associated spark streaming memory. > > I have been running two Spark Streaming jobs concurrently. The jobs read > data from Kafka with a batch interval of 1 minute, performs aggregation, and > sinks the computed data to MongoDB using using stratio-mongodb connector. > > I have setup the spark standalone cluster on AWS. My setup is configured as > follows: I have a four-node cluster. One node as a master, and the rest > 3-nodes as workers, while each worker has only one executor, with 2-cores > and 8GB of RAM. > > Currently, I am processing seven-hundred thousand JSON events, every minute. > After running the jobs for 3-4 hours, I have observed that the memory > consumption keeps growing, exiting one of the jobs. > > Despite setting /spark.cleaner.ttl/ for 600 seconds, and having used > /rdd.unpersist/ method at the end of the job. I am not able to understand > why the memory consumption keeps growing over time. I am unable solve this > problem. I would appreciate if someone can help me solve or provide > redirections as to why this is happening. > > Thank you. > > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Memory-grows-exponentially-tp27308.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe e-mail: user-unsubscr...@spark.apache.org >
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