We need to deal with 2 types of data structures in Spark – RDD and Data Frames. We will see both in detail as we proceed further. RDD is there for quite some time and it is the low-level data structure which spark uses to distribute the data between tasks while data is being processed. …
In the earlier versions of Spark, we have core API at the bottom and all the higher level modules work with core API. Examples of core API are a map, reduce, join, groupByKey etc. But with Spark 2, Data Frames and Spark SQL has become the core module. Core – Transformations and Actions — APIs …
Let us have a quick review of Core APIs that are available in Spark. We will cover Data Frame APIs and Spark SQL at a later point in time. SparkContext exposes APIs such as textFile, sequenceFile to read data from files into a distributed collection called as RDD. RDD stands for Resilient Distributed Dataset and …
Let us understand how Spark Official Documentation is organized. Overview Start Documentation for Different Modules API Docs Cluster Overview under Deploying Submitting Applications Execution Frameworks Tuning and more
At ITVersity we provide a multi-node Spark Cluster. Let us understand some important details with respect to ITVersity labs. Click here to visit our labs. We have 10+ node cluster in which Spark is integrated with Hadoop ecosystem It has a total capacity of 80+ cores and 400+ GB Memory and sEveral terabytes of storage. …
In Hive, you can create a table using the STORED AS clause to specify the file format in which the table data will be stored. Here are the steps to create a table using the STORED AS clause in Hive: you could store the table data in ORC format by specifying STORED AS ORC. In …
Section 8:74.Creating Table using orc File Format – Order_items Read More »
