January 2019
Intermediate to advanced
322 pages
7h 29m
English
Content preview from Hands-On Deep Learning with Apache Spark
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Cluster mode using different managers
The following diagram shows how Spark applications run on a cluster. They are independent sets of processes that are coordinated by the SparkContext object in the Driver Program. SparkContext connects to a Cluster Manager, which is responsible for allocating resources across applications. Once the SparkContext is connected, Spark gets executors across cluster nodes.
Executors are processes that execute computations and store data for a given Spark application. SparkContext sends the application code (which could be a JAR file for Scala or .py files for Python) to the executors. Finally, it sends the tasks to run to the executors:
Figure 1.12
To isolate applications from each other, every Spark application ...
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