Table of Contents
What is difference of running the queries in the Hive and in Spark?
Hive provides schema flexibility, portioning and bucketing the tables whereas Spark SQL performs SQL querying it is only possible to read data from existing Hive installation. Hive provides access rights for users, roles as well as groups whereas no facility to provide access rights to a user is provided by Spark SQL.
What is Pyspark HiveContext?
Class HiveContext A variant of Spark SQL that integrates with data stored in Hive. Configuration for Hive is read from hive-site. xml on the classpath. It supports running both SQL and HiveQL commands.
What is the difference between sparkContext and SQLContext?
sparkContext is a Scala implementation entry point and JavaSparkContext is a java wrapper of sparkContext. SQLContext is entry point of SparkSQL which can be received from sparkContext. x.x, All three data abstractions are unified and SparkSession is the unified entry point of Spark.
Which is better hive or Spark?
Hive and Spark are both immensely popular tools in the big data world. Hive is the best option for performing data analytics on large volumes of data using SQLs. Spark, on the other hand, is the best option for running big data analytics. It provides a faster, more modern alternative to MapReduce.
What is SparkSession in Spark?
SparkSession is the entry point to Spark SQL. It is one of the very first objects you create while developing a Spark SQL application. As a Spark developer, you create a SparkSession using the SparkSession. builder method (that gives you access to Builder API that you use to configure the session).
What is Spark conf?
SparkConf is used to specify the configuration of your Spark application. This is used to set Spark application parameters as key-value pairs. For instance, if you are creating a new Spark application, you can specify certain parameters as follows: val conf = new SparkConf() .setMaster(“”local[2]””)
Which is better Hive or Spark?
What is the difference between Spark and MapReduce?
The primary difference between Spark and MapReduce is that Spark processes and retains data in memory for subsequent steps, whereas MapReduce processes data on disk. As a result, for smaller workloads, Spark’s data processing speeds are up to 100x faster than MapReduce.
What is SparkContext Spark conf?
Sparkcontext is the entry point for spark environment. For every sparkapp you need to create the sparkcontext object. In spark 2 you can use sparksession instead of sparkcontext. Sparkconf is the class which gives you the various option to provide configuration parameters.
What is the difference between hive on Spark and sparksql?
SparkSQL vs Spark API you can simply imagine you are in RDBMS world: Hive on Spark is similar to SparkSQL, it is a pure SQL interface that use spark as execution engine, SparkSQL uses Hive’s syntax, so as a language, i would say they are almost the same.
Do I need a hivecontext for my spark application?
If your Spark Application needs to communicate with Hive and you are using Spark < 2.0 then you will probably need a HiveContext if . For Spark 1.5+, HiveContext also offers support for window functions. // Scala import org.apache.spark. {SparkConf, SparkContext} Since Spark 2.x+, tow additions made HiveContext redundant:
What is hivemetastore in spark?
When SparkSQL uses hive. SparkSQL can use HiveMetastore to get the metadata of the data stored in HDFS. This metadata enables SparkSQL to do better optimization of the queries that it executes. Here Spark is the query processor.
What is sparkcontext in spark?
The SparkContext is used by the Driver Process of the Spark Application in order to establish a communication with the cluster and the resource managers in order to coordinate and execute jobs. SparkContext also enables the access to the other two contexts, namely SQLContext and HiveContext (more on these entry points later on).