Spark Jdbc Update
It allows you to use real-time transactional data in big data analytics and persist results for ad-hoc queries or reporting. jar) are on Maven Central Repository !!Refer to the blog for more details. This was the only option prior to the JDBC 4. Property kylin. the power of standard SQL and JDBC APIs with full ACID transaction capabilities and; the flexibility of late-bound, schema-on-read capabilities from the NoSQL world by leveraging HBase as its backing store; Apache Phoenix is fully integrated with other Hadoop products such as Spark, Hive, Pig, Flume, and Map Reduce. MySQL Connectors MySQL provides standards-based drivers for JDBC, ODBC, and. Complete mode requires all aggregate data to be preserved, and hence cannot use watermarking to drop intermediate state. Both of these (ResultSets and update counts) are considered by JDBC to be "results". In this article, we created a new Azure Databricks workspace and then configured a Spark cluster. jdbc("dburl", "tablename", "dbproperties"); I have million of data in this table and if I load the full table in spark dataframe and update the desired record then it will take more time and also it does not make sense because why I load the full table when I want to update. 1 GA and Service Pack 1 releases. This allows us to process data from HDFS and SQL databases like Oracle, MySQL in a single Spark SQL query Apache Spark SQL includes jdbc datasource that can read from (and write to) SQL databases. A repository in Maven holds build artifacts and dependencies of varying types. This reference guide is a work in progress. In the meantime, here is a short explanation about how to connect from Spark SQL to Oracle Database. Hi Guys, In this blog we'll be discussing about how to make a connection to presto server using JDBC, but before we get started let's discuss what Presto is. 1, subject to change in the future). com before the merger with Cloudera. Example of the db properties file would be something like shown below:. Access Apache Spark like you would a database - read, write, and update through a standard ODBC Driver interface. Redshift Data Source for Spark is a package maintained by Databricks, with community contributions from SwiftKey and other companies. In the meantime, here is a short explanation about how to connect from Spark SQL to Oracle Database. Here you will learn working scala examples of Snowflake with Spark Connector, Snowflake Spark connector “spark-snowflake” enables Apache Spark to read data from, and write data to Snowflake tables. 0 for SQL Server, a Type 4 JDBC driver that provides database connectivity through the standard JDBC application program interfaces (APIs) available in Java Platform, Enterprise Editions. 3 or later: INSERT; CREATE; DROP; Spark does not support UPDATE or DELETE syntax. zahariagmail. The driver achieves this by translating Open Database Connectivity (JDBC) calls from the application into SQL and passing the SQL queries to the underlying Impala engine. executeUpdate instead of PreparedStatement. Glue supports accessing data via JDBC, and currently the databases supported through JDBC are Postgres, MySQL, Redshift, and Aurora. here is link to a similar question : Spark Dataframes UPSERT to Postgres Table. hiveserver2. SQL engines for Hadoop differ in their approach and functionality. New features, Changes and Resolved issues. If you are already using JDBC applications with an earlier Impala release, you should update your JDBC driver, because the Hive 0. We'll walk through some code example and discuss Spark integration for JDBC data sources (DB2 and Big SQL) using examples from a hands-on lab. Before you use the Hadoop FS origin to read from non-HDFS systems, install all required file system application JAR files. You can choose from a wide range of options, including JDBC, eBean, and JPA. This project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. If both UPDATE and DELETE clauses are present, the first one in the statement must include [AND ]. Open Source Apache Spark is fast becoming the de facto standard for Big Data processing and analytics. Programming languages. These examples are extracted from open source projects. In the Spark documentation on JDBC connection, the explanation of all the properties are given in detail. As a part of the Spark installation, update the following properties to spark2-defaults from Ambari UI: spark. Python For Data Science Cheat Sheet PySpark - SQL Basics Learn Python for data science Interactively at www. options( Map("driver" -> Support Questions Find answers, ask questions, and share your expertise @Anuj Tanwar AFAIK updates are supported with spark jdbc. MySQL driver is a type 4 JDBC driver, so you just need to add the JAR file in Eclipse. When no predicate is provided, update the column values for all rows. Contribute to apache/spark development by creating an account on GitHub. We will show examples of JSON as input source to Spark SQL’s SQLContext. Is there any way to execute deletes and updates to an existing delta lake table when using a JDBC connection? Add comment. Easily Build BI Applications with Open Source, Interactive SQL. At Dataquest, we’ve released an interactive course on Spark, with a focus on PySpark. jar), Universal Connection Pool (ucp. CData JDBC Driver for Spark SQL 2019 CData JDBC Driver for Spark SQL 2019 - Build 19. What you can do it iterate over the dataframe/RDD using the foreachRDD() loop and manually update/delete the table using JDBC api. This page summarizes some of common approaches to connect to SQL Server using Python as programming language. The Spark connector for Azure SQL Database and SQL Server enables these databases to act as input data sources and output data sinks for Apache Spark jobs. Note Due to Oracle license restrictions, the Oracle JDBC driver is not available in the public Maven repository. 13 JDBC driver. In all the examples…. The driver process runs the user code on these executors. Why Hive is used inspite of Pig? The following are the reasons why Hive is used in spite of Pig’s availability: Hive-QL is a declarative language line SQL, PigLatin is a data flow language. Bradleyy, Xiangrui Mengy, Tomer Kaftanz, Michael J. In other words, MySQL is storage+processing while Spark’s job is processing only, and it can pipe data directly from/to external datasets, i. See the updated blog post for a tutorial and notebook on using the new MongoDB Connector for Apache Spark. jdbc(jdbcUrl, "tempCar", jdbcProp) Now I have all the records from the csv file into the "tempCar" table , but I cannot find an easy way in Spark to update these records in table. CCA 175 Hadoop and Spark Developer Exam Preparation - Problem Scenario 5 PLEASE READ THE INTRODUCTION TO THIS SERIES. Spark and SparkSQL. mode(SaveMode. Regression test examples. Download and install the drivers. conf to include the 'phoenix--client. They provide key elements of a data lake—Hadoop Distributed File System (HDFS), Apache Spark, and analytics tools—deeply integrated with SQL Server and fully supported by Microsoft. NET developer ecosystem with. com: matei: Apache Software Foundation. Sign up import org. And if you want the minimap on the right, you can download Netbeans Almarean: 2018-03-14: 4. 1, 2, or 3 WHEN clauses may be present; at most 1 of each type: UPDATE/DELETE/INSERT. The Oracle Driver. This library naturally wraps JDBC APIs and provides you easy-to-use and very flexible APIs. executor; Creation of a start a script to call the script listed above. This recipe shows how Spark DataFrames can be read from or written to relational database tables with Java Database Connectivity (JDBC). dll and is specific to the Windows platform. 6 Last update 20. It enables unmodified Hadoop Hive queries to run up to 100x faster on existing deployments and data. This example assumes the mySQL connector JDBC jar file is located in the same directory as where you are calling spark-shell. 0 for SQL Server, a Type 4 JDBC driver that provides database connectivity through the standard JDBC application program interfaces (APIs) available in Java Platform, Enterprise Editions. If there is a database system that I forgot to add, add a comment and I’ll update the article. Xiny, Cheng Liany, Yin Huaiy, Davies Liuy, Joseph K. Thank you for pointing this out. The TAR archive contains the latest 11. In this video lecture we learn how to install/upgrade/setup spark 2 in Cloudera quick start vm. Learn how to connect an Apache Spark cluster in Azure HDInsight with an Azure SQL database and then read, write, and stream data into the SQL database. Spark SQLContext allows us to connect to different Data Sources to write or read data from them, but it has limitations, namely that when the program ends or the Spark shell is closed, all links to the datasoruces we have created are temporary and will not be available in the next session. Moreover it seems to look as it is limited to the logical conjunction (no IN and OR I am afraid) and simple predicates. Spark SQL: Relational Data Processing in Spark Michael Armbrusty, Reynold S. It thus gets tested and updated with each Spark release. April 2016 Newest version Yes Organization not specified URL Not specified License not specified Dependencies amount 11 Dependencies hive-common, hive-service, hive-serde, hive-metastore, hive-shims, commons-logging, httpclient, httpcore, libthrift, zookeeper. For queries that return multiple results the JDBC spec requires execute() to be used. Check out the Release History Notes for JDBC for Apache Spark SQL. Apache Spark is a fast and general-purpose cluster computing system. If there is a database system that I forgot to add, add a comment and I’ll update the article. Sqooping Data from Oracle Using Spark Scala. Vectorization will be turned off for merge operations. This reduces round-trips to the database by fetching multiple rows of data each time data is fetched. Microsoft® Spark ODBC Driver enables Business Intelligence, Analytics and Reporting on data in Apache Spark. Your request was unable to be processed org. Before version 3. Published 2017-03-28. Spark DataFrames (as of Spark 1. If “ssl” = true, the “port” should be Kylin server’s HTTPS port; If “port” is not specified, the driver will use default port: HTTP 80, HTTPS 443;. CCA 175 based on Sqoop export/import, data ingestion, and Spark transformations. Spark SQL MySQL (JDBC) Python Quick Start Tutorial. 3 running on another host This host is running CentOS 6. SQL Server Big Data cluster bundles Spark and HDFS together with SQL server. Apache Spark is a unified analytics engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing. The driver is designed to access Spark SQL via the Thrift JDBC server. Doing a database update, as opposed to an insert is useful, particularly when working with streaming applications which may require revisions to previously stored data. To use the Oracle JDBC driver with Maven, you have to download and install it into your Maven local repository manually. For example, you can connect to Cassandra using spark_read_source(). A Spark Streaming application will then consume those tweets in JSON format and stream them. managing-clusters. You can vote up the examples you like and your votes will be used in our system to produce more good examples. How to Change Schema of a Spark SQL DataFrame? By Chih-Ling Hsu. 4 for Cloudera Enterprise. MySQL Connectors MySQL provides standards-based drivers for JDBC, ODBC, and. ScalikeJDBC Just write SQL and get things done! ScalikeJDBC is a tidy SQL-based DB access library for Scala developers. , reporting or BI) queries, it can be much faster as Spark is a massively parallel system. Download the Microsoft JDBC Driver 6. Franklinyz, Ali Ghodsiy, Matei Zahariay yDatabricks Inc. 4 onwards there is an inbuilt datasource available to connect to a jdbc source using dataframes. Problem scenario 19: You have been given following mysql database details as well as other info. I have quite a few examples on this website, just see the "Related" section for those. 자주 이용하는 방식은 Mysql Connection관리와 key 중복이 발생할때 update를 하기 위해서 아래 두가지 방식을 많이 사용했다. Note: Don't use Cloudera Impala ODBC driver v2. We’re going to use mySQL with Spark in this tutorial, but you can apply the concepts presented here to any relational database which has a JDBC driver. Bradley†, Xiangrui Meng†, Tomer Kaftan‡, Michael J. It has built in support for Hive, Avro, JSON, JDBC, Parquet, etc. jar' Note that for Phoenix versions 4. Accessing SnappyData Tables from any Spark (2. 1 GA and Service Pack 1 releases. In your case, I wouldn't use dataframes at all for your delete operation, I would just parallelize the dates and send multiple delete statements in a map function. Use HDInsight Spark cluster to read and write data to Azure SQL database. However, Hive is planned as an interface or convenience for querying data stored in HDFS. MySQL Connectors MySQL provides standards-based drivers for JDBC, ODBC, and. getConnection() statement. 1 and is still supported. JDBC and Glue. Using Apache Spark and MySQL for Data Analysis Using a real-world example and code samples, the author shows how Sparke and. In Impala 2. According to the Spark FAQ, the largest known cluster has over 8000 nodes. Spark is the core component of Teads's Machine Learning stack. MIT CSAIL zAMPLab, UC Berkeley ABSTRACT Spark SQL is a new module in Apache Spark that integrates rela-. Not all the Hive syntax are supported in Spark SQL, one such syntax is Spark SQL INSERT INTO Table VALUES which is not supported. Hi, Has someone tried using Spark Streaming with MySQL (or any other database/data store)? I can write to MySQL at the beginning of the driver. Update: here is the 200 long slides presentation I made for Oracle Week 2016: it should cover most of the information new comers need to know about spark. It is true. Additional Oracle Performance Extensions. In all the examples…. Writing and Reading SQLite BLOB – we will show you how to update the SQLite BLOB data into a table and query BLOB data for displaying. Running queries and analysis on structured databases is a standard operation and has been in place for decades. The DataFrames can also be saved to the database by using DataFrameWriter APIs. Spark SQL: Spark SQL supports only JDBC and ODBC. Output mode must be Append or Update. Introduction. The Spark SQL developers welcome contributions. 12 driver that was formerly the only choice is not compatible with Impala 2. springframework. It also supports streaming data with iterative algorithms. Interacting with a stream. The system caters to the Personnel Administration, Payroll and other Accounts activities of Government Establishments. JavaBeans and Scala case classes representing. MySQL can only use one CPU core per query, whereas Spark can use. IGNITE FOR SPARK; Ignite RDD and DataFrames: Apache Ignite provides an implementation of Spark RDD abstraction and DataFrames which allows to easily share state in memory across multiple Spark jobs and boost Spark's applications performance. Updating data in database in Spark using Scala. We can read the data of a SQL Server table as a Spark DataFrame or Spark temporary view and then we can apply Spark transformations and actions on the data. Learn how to create a new interpreter. Before executing following example, make sure you have the follow. 0 update 20190312 or earlier requires Java 8. These examples are extracted from open source projects. Run your Apache Spark programs without changes because the TIBCO ComputeDB in-memory database is 100% compatible with Apache Spark. This library naturally wraps JDBC APIs and provides you easy-to-use and very flexible APIs. even though there was heavy database communication back and forth there was no ORM used e. 4 JDBC author Talend Documentation Team EnrichVersion 6. This project helped me improve my knowledge on distributed systems and gave me exposure of working on a team on large projects. Spark SQL MySQL (JDBC) Python Quick Start Tutorial. 1 Thrift server. There should be atleast as many partitions as the number of the cores available for the Spark tasks. Athena is serverless, so there is no infrastructure to setup or manage, and you can start analyzing data immediately. JDBC batch update JDBC Update is used when you want to save all the modify or changes values in a database. Thanks to the native JDBC support by Spark SQL, users can access most database via their JDBC drivers. Blog The Interactive News Platform for Everyone Oracle Bulkload. Examples use Scala and the Spark shell in a BigInsights 4. To connect to Oracle from Spark, we need JDBC Url, username, password and then the SQL Query that we would want to be executed in oracle to fetch the data into Hadoop using spark > update > package. Spring JDBC UPDATE. Spark 实现MySQL update操作 背景. 5 and Spark 1. In this article I'll be taking an initial look at Spark Streaming, a component within the overall Spark platform that allows you to ingest and process data in near real-time whilst keeping the. No changes. Spark supports text files (compressed), SequenceFiles, and any other Hadoop InputFormat as well as Parquet Columnar storage. Spark SQL APIs can read data from any relational data source which supports JDBC driver. NET, which is actively used by millions of developers, with over 1 million new developers coming to the platform in the last year. jdbc sparksql table. Spark DataFrames (as of Spark 1. metastoreUri - From Hive > General, get and use the value of this property: hive. Update any version 1 connections to use the new version. Artifact hive-jdbc Group org. JDBC stops reconnecting and throws an Exception if all the endpoints are unreachable. 3 (jdbc) and 2. Play Framework makes it easy to build web applications with Java & Scala. Tableau Spark SQL Setup Instructions 1. JDBC - Update Records Example - This chapter provides an example on how to update records in a table using JDBC application. The HWC library loads data from LLAP daemons to Spark executors in parallel, making it more efficient and scalable than using a standard JDBC connection from Spark to Hive. zahariagmail. 0, the first step is no longer needed, as the driver manager attempts to load a suitable JDBC driver from classpath. Spark is an analytics engine for big data processing. Tune the JDBC fetchSize parameter. Managing transaction – this tutorial shows you how to manage SQLite transaction using Java JDBC API such as setAutoCommit, commit, and rollback. The driver is designed to access Spark SQL via the Thrift JDBC server. I have not tested with Spark 2. 68K views2017-12-24 0 raghavendra12 2017-08-30 0 Comments Hi, Please provide jdbc connection string or driver implementation for greenplum. We are able to utilize built in triggers to specify when to update the results. Download the Microsoft JDBC Driver 6. UPDATE: There was a further discussion regarding this topic, %AddJar should add the jar to the classpath and according to the comments above the name was also found. Spark can be configured with multiple cluster managers like YARN, Mesos etc. I used a spark job to store the csv records (as-is) in a temporary table "tempCar" , carData. 0 update 20190312 or earlier requires Java 8. ) Advantages of Apache. Use of HiveServer2 is recommended as HiveServer1 has several concurrency issues and lacks some features available in HiveServer2. Spark has several quirks and limitations that you should be aware of when dealing with JDBC. The HWC library loads data from LLAP daemons to Spark executors in parallel, making it more efficient and scalable than using a standard JDBC connection from Spark to Hive. The JDBC project is proud to announce the latest version 42. We can sqoop the data from RDBMS tables into Hadoop Hive table without using SQOOP. For the reason that I want to insert rows selected from a table. Sink is the extension of the BaseStreamingSink contract for streaming sinks that can add batches to an output. Download operating system-specific drivers for Windows and Linux that allow you to connect to a wide range of data sources. Apache Spark. Make your changes and simply hit refresh!. How to do CDC in Hadoop. jar and ojdbc6. 11) Creation of a script to update the extraClassPath for the properties spark. Doing a database update, as opposed to an insert is useful, particularly when working with streaming applications which may require revisions to previously stored data. The Spark SQL Thrift server uses a JDBC and an ODBC interface for client connections to DSE. Spark SQL is developed as part of Apache Spark. December 2005 Newest version Yes Organization not specified URL Not specified License not specified Dependencies amount 0 Dependencies No dependencies There are maybe transitive dependencies!. This video along with the next couple of other tutorial videos, I will cover following. PostgreSQL. Moreover it seems to look as it is limited to the logical conjunction (no IN and OR I am afraid) and simple predicates. Blog The Interactive News Platform for Everyone Oracle Bulkload. Spark Project Hive Thrift Server Last Release on Dec 17, 2019 19. Java Database Connectivity (JDBC) is an application program interface (API) packaged with the Java SE edition that makes it possible to standardize and simplify the process of connecting Java applications to external, relational database management systems (RDBMS). If a schema is not provided, then the default "public" schema is used. Can we use UPDATE/DELETE queries in Databricks with SparkSQL since UPDATE/DELETE have been added in hive 0. The Hive Warehouse Connector maps most Apache Hive types to Apache Spark types and vice versa, but there are a few exceptions that you must manage. jar), Universal Connection Pool (ucp. Install Tableau DevBuild 8. This library naturally wraps JDBC APIs and provides you easy-to-use and very flexible APIs. Spark SQL Libraries. ODBC is one of the most established APIs for connecting to and working with databases. 5 with Spark 2. If this value is set too low then your workload may become latency-bound due to a high number of roundtrip requests between Spark and the external database in order to fetch the full result set. Property kylin. HiveWarehouseSession API operations As a Spark developer, you execute queries to Hive using the JDBC-style HiveWarehouseSession API that supports Scala, Java, and Python. executeUpdate for DDLs. Design, modeling and coding an application to manager pages in multi-languages using the XML and XSLT technology making in C# using Microsoft SQL Server through IIS. Name Email Dev Id Roles Organization; Matei Zaharia: matei. To connect to Oracle from Spark, we need JDBC Url, username, password and then the SQL Query that we would want to be executed in oracle to fetch the data into Hadoop using spark > update > package. Using an Impala JDBC driver to Query Apache Kudu Introduction Apache Kudu is columnar storage manager for Apache Hadoop platform, which provides fast analytical and real time capabilities, efficient utilization of CPU and I/O resources, ability to do updates in place and an evolvable data model that’s simple. springframework. Spark Streaming is a Spark component that enables processing of live streams of data. "Since I don’t have a blog and you don’t allow anonymous comments I thought I’d shoot a quick email with a question/concern. Spark supports text files (compressed), SequenceFiles, and any other Hadoop InputFormat as well as Parquet Columnar storage. dll and is specific to the Windows platform. need help specifying potentially reserved words as strings in postgres query. It includes basic PySpark code to get you started with using Spark Data Frames. We've also added several new table and matrix improvements based on the feedback you've given us on our UserVoice forum. createOrReplaceTempView("cardetails") spark. You can vote up the examples you like and your votes will be used in our system to produce more good examples. Make your changes and simply hit refresh!. Use HDInsight Spark cluster to read and write data to Azure SQL database. For the reason that I want to insert rows selected from a table. Spark setup. Apache Spark is a fast and general-purpose cluster computing system. 7 installed. I'm using the Simba Spark JDBC 4. Let’s show examples of using Spark SQL mySQL. JDBC - Delete Records Example - This chapter provides an example on how to delete records from a table using JDBC application. In Vertica 9. Internally, Spark SQL uses this extra information to perform extra optimizations. Spark also has a useful JDBC reader, and can manipulate data in more ways than Sqoop, and also upload to many other systems than just Hadoop. url parameter. SQL Server comes in various flavours. Certain DataFrame APIs invoke DDLs such as CREATE TABLE and DROP TABLE under the covers. hive Version 1. Question by ALincoln · May 12, Does Spark or Spark JDBC support connection to Google Cloud BigQuery tables? If yes, What are the operations are allowed to perform on those tables? 1 Answer. We've also added several new table and matrix improvements based on the feedback you've given us on our UserVoice forum. Some of my readers asked about saving Spark dataframe to database. Since the time when Hive, HBase, Cassandra, Pig, and MapReduce came into existence, developers felt the need of having a tool that can interact with RDBMS server to import and export the data. Unlike other data sources, when using JDBCRDD, ensure that the database is capable of handling the load of parallel reads from apache. Apache Spark is the recommended out-of-the-box distributed back-end, or can be extended to other distributed backends. If you have questions about the system, ask on the Spark mailing lists. 0 of the JDBC API, there was no standard way of retrieving key values from databases that supported auto increment or identity columns. 3 release represents a major milestone for Spark SQL. 10/03/2019; 7 minutes to read +1; In this article. Stay tuned to this blog for updates on other components of the Apache Spark 1. cs to call SPs rather than specific calls to the table? Thanks, Dorothy. Thank you for pointing this out. Use a valid URL in the JDBC connection string when you write application code or configure BI tools. Also we will try to explore scenarios where we. Blog The Interactive News Platform for Everyone Oracle Bulkload. The YugabyteDB JDBC driver extends PgJDBC to add support for distributed SQL databases created in YugabyteDB universes, including cluster awareness and load balancing. Via JDBC you create a connection to the database, issue database queries and update as well as receive the results. 2 JDBC Thin driver (ojdbc7. For queries that return multiple results the JDBC spec requires execute() to be used. If both UPDATE and DELETE clauses are present, the first one in the statement must include [AND ]. In this video lecture we learn how to install/upgrade/setup spark 2 in Cloudera quick start vm. RDDs are a unit of compute and storage in Spark but lack any information about the structure of the data i. Moreover, I have not had any problems using this database with Python. hive Version 1. With older JDBC drivers for MySQL, you could always use a. Spark introduced dataframes in version 1. This reduces round-trips to the database by fetching multiple rows of data each time data is fetched. 3 and enriched dataframe API in 1. Jdbc connection url, username, password and connection pool maximum connections are exceptions which must be configured with their special Hive Metastore configuration properties. Spark has several quirks and limitations that you should be aware of when dealing with JDBC. Apache Spark is the recommended out-of-the-box distributed back-end, or can be extended to other distributed backends. Apache Spark is the open standard for fast and flexible general purpose big-data processing, enabling batch, real-time, and advanced analytics on the Apache Hadoop platform. To run this example, you need to install the appropriate Cassandra Spark connector for your Spark version as a Maven library. However, from SnappyData 1. com before the merger with Cloudera. Thank you for pointing this out. It is similar in concept to ODBC (Oracle DataBase Connectivity) and JDBC (Java DataBase Connectivity). Spark SQL includes a server mode with industry standard JDBC and ODBC connectivity. Certain DataFrame APIs invoke DDLs such as CREATE TABLE and DROP TABLE under the covers. Spark SQL: Relational Data Processing in Spark Michael Armbrusty, Reynold S. Moreover it seems to look as it is limited to the logical conjunction (no IN and OR I am afraid) and simple predicates. Manage your big data environment more easily with Big Data Clusters. Java SQL FAQ: Can you provide a Java PreparedStatement example that shows how to use a SQL UPDATE? Sure. With Spark, you can get started with big data processing, as it has built-in modules for streaming, SQL, machine learning and graph processing. createStatement();. no Hibernate, JPA. It is a Java-based data access technology used for Java database connectivity. Start the spark shell with -jars argument $ SPARK_HOME / bin / spark - shell -jars mysql-connector-java-5. You can update statements and write DataFrames to partitioned Hive tables, perform batch writes, and use HiveStreaming. So if you pass a date in a filter or where clause it won't load all of the data in the dataframe. (For background on the HDFS_FDW and how it works with Hive, please refer to the blog post Hadoop to Postgres - Bridging the Gap.