Demystifying inner-workings of Apache Spark. The Internals of Apache Spark . apache-spark-internals
- Enabling Dynamic Allocation of Executors. Spark on YARN has the ability to scale the number of executors used for a Spark application dynamically. Using Amazon EMR release version 4.4.0 and later, dynamic allocation is enabled by default.
- Spark standalone and YARN only: --executor-cores NUM Number of cores per executor. (Default: 1 in YARN mode, or all available cores on the worker in standalone mode) YARN-only: --driver-cores NUM Number of cores used by the driver, only in cluster mode (Default: 1).
The number of executors to be created. executor-memory. As specified by the --num-executors parameter, two executors are initiated on work nodes. Each executor is allocated with 2 GB memory (specified by the --executor-memory parameter) and supports a maximum of 2 concurrent tasks...
- experiment, we set the number of executors to be 8. We ran a number of iterative applications provided in HiBench , including LDA, SVM, PageRank and KMeans. Figure 1(a) shows the accumulative job progress achieved with the stati-cally allocated resources. The result also shows that it takes 20% time for the SVM job to achieve progress by 90%,
Aug 28, 2020 · The main configuration parameter used to request the allocation of executor memory is spark.executor.memory. Spark running on YARN, Kubernetes or Mesos, adds to that a memory overhead to cover for additional memory usage (OS, redundancy, filesystem cache, off-heap allocations, etc), which is calculated as memory_overhead_factor * spark.executor.memory (with a minimum of 384 MB).
- The Docker Container Executor (DCE) allows the YARN NodeManager to launch YARN containers into Docker containers. Users can specify the Docker images they want for their YARN containers. These containers provide a custom software environment in which the user’s code runs, isolated from the software environment of the NodeManager.
Spark is a set of libraries and tools available in Scala, Java, Python, and R that allow for general purpose distributed batch and real-time computing and processing. Spark is available for use in on the Analytics Hadoop cluster in YARN.
- Jul 20, 2016 · We’re using a similar setup as config C (our best result so far with two servers), for this config, called config G: 1 producer engine, 2 executor engine. Note that we’re also adding a ‘queue server’ to the mix now, that’s using a c3.8xlarge machine (32 vCPUs, 60 GiB RAM) like the executor engine server.
May 14, 2019 · spark-shell --master yarn \ --conf spark.ui.port=12345 \ --num-executors 3 \ --executor-cores 2 \ --executor-memory 500M. As part of the spark-shell, we have mentioned the num executors. They indicate the number of worker nodes to be used and the number of cores for each of these worker nodes to execute tasks in parallel.
- Spark submit supports several configurations using --config, these configurations are used to specify Application configurations, shuffle parameters, runtime configurations. A maximum number of executors to use when dynamic allocation is enabled. spark.executor.extraJavaOptions.
View cluster information in the Apache Spark UI. Detailed information about Spark jobs is displayed in the Spark UI, which you can access from: The cluster list: click the Spark UI link on the cluster row. The cluster details page: click the Spark UI tab. The Spark UI displays cluster history for both active and terminated clusters.
- I have total 9 executors launched with 5 thread for each. The job has run fine until the very end. When it reaches 19980/20000 tasks succeeded, it suddenly failed the last 20 tasks and I lost 2 executors. The spark did launched 2 new executors and finishes the job eventually by reprocessing the 20 tasks.
num_executors (Optional [int]) – Number of executors to launch for this session. archives (Optional [List [str]]) – URLs of archives to be used in this session. queue (Optional [str]) – The name of the YARN queue to which submitted. name (Optional [str]) – The name of this session. spark_conf (Optional [Dict [str, Any]]) – Spark ...