Does Spark use HDFS?

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark’s standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. Some of them are listed on the Powered By page and at the Spark Summit.

Does Apache Spark need HDFS?

Yes, Apache Spark can run without Hadoop, standalone, or in the cloud. Spark doesn’t need a Hadoop cluster to work. Spark can read and then process data from other file systems as well. HDFS is just one of the file systems that Spark supports.

Does Spark support replication?

There is also support for persisting datasets on disk, or replicated across the cluster.

How does Apache Spark run on a cluster?

Spark applications run as independent sets of processes on a cluster, coordinated by the SparkContext object in your main program (called the driver program). Once connected, Spark acquires executors on nodes in the cluster, which are processes that run computations and store data for your application.

How Spark reads data from HDFS?

Spark uses partitioner property to determine the algorithm to determine on which worker that particular record of RDD should be stored on. When Spark reads a file from HDFS, it creates a single partition for a single input split. Input split is set by the Hadoop InputFormat used to read this file.

What is replication in Spark?

1. 0. Spark is a cluster computation engine, it does not replicates data or stored data implicitly. Spark processing is based on rdd, if due to node failure any of the data partition is lost it can be recalculated using DAG. Though while persisting data you can store the data in memory or disk.

What is the replication factor in Spark?

The doc details a number of storage levels and what they mean, but they’re fundamentally a configuration shorthand to point Spark to an object which extends the StorageLevel class. You can thus define your own with a replication factor of up to 40.

How does Spark write data into HDFS?

Write the elements of the dataset as a text file (or set of text files) in a given directory in the local filesystem, HDFS or any other Hadoop-supported file system. Spark will call toString on each element to convert it to a line of text in the file.