Both provide compatibilities for each other. from os.path import abspath from pyspark.sql import SparkSession from pyspark.sql import Row # warehouse_location points to the default location for managed databases and tables warehouse_location = abspath ('spark-warehouse') spark = SparkSession \ . builder \ . appName ("Python Spark SQL Hive integration example") \ .

Spark hive integration

0 votes . 1 view. asked Jul 10, 2019 in Big Data Hadoop & Spark by Eresh Kumar (32.3k points) Is there any code for the Spark Integration? apache-spark; hadoop; spark; spar-integration; 1 Answer. 0 votes . answered Jul 10, 2019 There are two really easy ways to query Hive tables using Spark. 1.

There are two really easy ways to query Hive tables using Spark. 1. Using SparkSQLContext: You can create a SparkSQLContext by using a SparkConf object to specify the name of the application and some other parameters and run your SparkSQL queries When a Spark job accesses a Hive view, Spark must have privileges to read the data files in the underlying Hive tables. Currently, Spark cannot use fine-grained privileges based on the columns or the WHERE clause in the view definition.

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To read Hive external tables from Spark, you do not need HWC. Spark uses native Spark to read external tables. Spark SQL supports a different use case than Hive. Compared with Shark and Spark SQL, our approach by design supports all existing Hive features, including Hive QL (and any future extension), and Hive’s integration with authorization, monitoring, auditing, and other operational tools. 1.4 Other Considerations Hive Integration in Spark. From very beginning for spark sql, spark had good integration with hive. Hive was primarily used for the sql parsing in 1.3 and for metastore and catalog API’s in later versions.
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Accessing Hive from Spark. Right now Spark SQL is very coupled to a specific version of Hive for two primary reasons. Metadata: we use the Hive Metastore client to retrieve information about tables in a metastore. Execution: UDFs, UDAFs, SerDes, HiveConf and various helper functions for configuration. A Hive metastore warehouse (aka spark-warehouse) is the directory where Spark SQL persists tables whereas a Hive metastore (aka metastore_db) is a relational database to manage the metadata of the persistent relational entities, e.g.

The HWC library loads data from LLAP daemons to Spark executors in parallel. This process makes it more efficient and adaptable than a standard JDBC connection from Spark to Hive.
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SAP HANA is expanding its Big Data solution by providing integration to Apache Spark using the HANA smart data access technology.

We will be using the new (in Apache NiFi 1.5/HDF 3.1 Spark is integrated really well with Hive, though it does not include much of its dependencies and expects them to be available in its classpath. Jun 23, 2017 Hive Integration in Spark. From very beginning for spark sql, spark had good integration with hive.

Spark integration with Hive in simple steps: First, how to integrate with Spark and Hive in a Hadoop Cluster with below simple steps: 1. Copied Hive-site.xml file into $SPARK_HOME/conf Directory. (After copied hive-site XML file into Spark configuration path then Spark to get Hive Meta store information) 2.Copied Hdfs-site.xml file into $SPARK_HOME/conf Directory.