Spark Hbase Example Scala

The Certified Big Data Hadoop and Spark Scala course by DataFlair is a perfect blend of in- depth theoretical knowledge and strong practical skills via implementation of real life projects to give you a headstart and enable you to bag top Big Data jobs in the industry. SparkHbasetoHbase. {HBaseAdmin, Result} import org. This tutorial will teach you how to set up a full development environment for developing and debugging Spark applications. Spark RDD to read and write from HBase. scala transfers the data saved in hbase into RDD[String] which contains columnFamily, qualifier, timestamp, type, value. With the advent of DataFrames in Spark 1. Apache Spark is a distributed processing framework and programming model that helps you do machine learning, stream processing, or graph analytics using Amazon EMR clusters. Phoenix Spark Example. HQL, Pig Latin, HDFS, Flume and HBase adds to his forte. There are no primitive types in Scala, Everything is an object in Scala. 3 versions due to PHOENIX-2040 being missed (here is the internal jira). 0, and Elasticsearch 6. Today, in this Hbase Command tutorial, we will see Data Manipulation HBase Command. A Write Ahead Logs (WAL) is like a journal log. DefaultSource does not allow create table as select looking for sample snippet. To join one or more datasets with join() function. With the Spark Thrift Server, you can do more than you might have thought possible. Prerequisites. 0 GA (hadoop 2. The Apache Spark and Scala training tutorial offered by Simplilearn provides details on the fundamentals of real-time analytics and need of distributed computing platform. Although we used Kotlin in the previous posts, we are going to code in Scala this time. HBase Tutorial. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy. Apache Spark shell scala examples. It shows how to register UDFs, how to invoke UDFs, and caveats regarding evaluation order of subexpressions in Spark SQL. Run the included Spark (scala) code against the HBase Snapshot. I read "SPARK-ON-HBASE: DATAFRAME BASED HBASE CONNECTOR" ( Github) and saw the parameters for running spark-shell. There are several cases where you would not want to do it. I will share my day-to-day experiences with technology ranging from java/c/c++/scala to spark, hbase and other big data technologies. Efficient bulk load of HBase using Spark. Let us explore the objectives of spark streaming in the next section. If you want Drill to interpret the underlying HBase row key as something other than a byte array, you need to know the encoding of the data in HBase. scala return only the value of first column in the result. Here are some ways to write data out to HBase from Spark: HBase supports Bulk loading from HFileFormat files. If you don’t know HBase, check out this excellent presentation by Ian Varley. Have you tried on HDP 2. I have seen couple of good example at HBase Github. 12, Spark 2. Let us explore the Apache Spark and Scala Tutorial Overview in the next section. In this article, we will check create tables using HBase shell commands and examples. But with the Put command, you would be able to insert a record every time and if ever you need to do a bulk insert, you will find the issue. Why I said "near" real-time? Because data processing takes some time, few milliseconds. Hadoop is an open source framework. Style and approach This book is an extensive guide to Apache Spark modules and tools and shows how Spark's functionality can be extended for real-time processing and storage with worked examples. Is Apache Spark going to replace hadoop? If you are into BigData analytics business then, should you really care about Spark? I hope this blog post will help to answer some of your questions which might have coming to your mind these days. The method used does not rely on additional dependencies, and results in a well partitioned HBase table with very high, or complete, data locality. The Apache Spark and Scala training tutorial offered by Simplilearn provides details on the fundamentals of real-time analytics and need of distributed computing platform. newAPIHadoopRDD is the API available in Spark to create RDD on hbase, configurations need to passed as shown below. kafka-console producer writes to a one or more topics and Spark streaming consumer consumes the messages from the topic and writes the count of each word to an HBase table. You can use Spark to call an HBase API to perform operations on HBase table1 and write the data analysis result oftable1 to HBase table2. Apache Spark is an open source data processing framework which can perform analytic operations on Big Data in a distributed environment. Apache Spark tutorial introduces you to big data processing, analysis and ML with PySpark. HBase provides random, realtime read/write access to the Bigdata. Also, I am anxious to try HBase Connector with HDP 2. 12, Spark 2. Hopefully, this simple example could help. With the Spark Thrift Server, you can do more than you might have thought possible. To understand this article, users need to have knowledge of hbase, spark, java and scala. Inside HBASE-13992. Spark can work with multiple formats, including HBase tables. 6K Views Sandeep Dayananda Sandeep Dayananda is a Research Analyst at Edureka. Apache Spark is an open-source parallel processing framework that supports in-memory processing to boost the performance of big-data analytic applications. Authors of examples: Matthias Langer and Zhen He Emails addresses: m. 10/02/2019; 5 minutes to read +3; In this article. It shows how to register UDFs, how to invoke UDFs, and caveats regarding evaluation order of subexpressions in Spark SQL. The following package is available: mongo-spark-connector_2. I could not find a clean example of dumping HFile using Spark for bulk loading. You create a dataset from external data, then apply parallel operations to it. This time, we are going to use Spark Structured Streaming (the counterpart of Spark Streaming that provides a Dataframe API). Dataframe will be created when you parse this RDD on case class. SHC is a well maintained package from Hortonworks to interact with HBase from Spark. In the beginning of the tutorial, we will learn how to launch and use the Spark shell. To join one or more datasets with join() function. Apache HBase is typically queried either with its low-level API (scans, gets, and puts) or with a SQL syntax using Apache Phoenix. Hbase was created by using JAVA , It was modeled on the basis of Google Big table. HBase is an essential component of the Hadoop ecosystem that. 3) Apache Spark 1. Applicable Versions. Note that Spark artifacts are tagged with a Scala version. It was built on top of Hadoop MapReduce and it extends the MapReduce model to efficiently use more types of computations which includes Interactive Queries and Stream Processing. It’s not common to see DataFrames being coded in Scala against the Spark framework to work with ETL in HBase. To help you learn Scala from scratch, I have created this comprehensive guide. We use cookies for various purposes including analytics. leftOuterJoin() 1. Following we present examples of how you can run your program with spark-submit both when your application is a Java/Scala program or a Python script. Run the included Spark (scala) code against the HBase Snapshot. Apache Spark Tutorial Following are an overview of the concepts and examples that we shall go through in these Apache Spark Tutorials. Before getting started, let us first understand what is a RDD in spark? RDD is abbreviated to Resilient Distributed Dataset. For the remaining of this documentation we will focus on Scala examples for now. 2 apache Spark These are the challenges that Apache Spark solves! Spark is a lightning fast in-memory cluster-computing platform, which has unified approach to solve Batch, Streaming, and Interactive use cases as shown in Figure 3 aBoUt apachE spark Apache Spark is an open source, Hadoop-compatible, fast and expressive cluster-computing platform. 1 pre installed (How to install Spark on Ubuntu 14. He is familiar with technology like Scala, Spark Kafka, Cassandra, Dynamo DB, Akka & many more. It happened to be difficult to find some ready to play with schema and data to load. 4 onwards there is an inbuilt datasource available to connect to a jdbc source using dataframes. This post will help you get started using Apache Spark Streaming with HBase on the MapR Sandbox. You want to analyze a large amount of data on the same Big Data (Hadoop/Spark) cluster where the data are stored (in, say, HDFS, HBase, Hive, etc. Example 2-4. It will help you to understand, how join works in spark scala. Our Hadoop tutorial is designed for beginners and professionals. Notably, with HBASE-13992, I was able to add Spark and Scala code to the Apache HBase project for the first time ever. This tutorial will : Explain Scala and its features. HBase is a Hadoop project which is Open Source, distributed Hadoop database which has its genesis in the Google'sBigtable. , in our case default values for local server work. Apache Spark. Applications that run on PNDA are packaged as tar. Currently it is compiled with Scala 2. , in our case default values for local server work. Apache Spark and Python for Big Data and Machine Learning Apache Spark is known as a fast, easy-to-use and general engine for big data processing that has built-in modules for streaming, SQL, Machine Learning (ML) and graph processing. This self-paced guide is the “Hello World” tutorial for Apache Spark using Databricks. ) Build project: mvn clean package b. This code will read the HBase snapshot, filter records based on rowkey range (80001 to 90000) and based on a timestamp threshold (which is set in the props file), then write the results back to HDFS in HBase format (HFiles/KeyValue). Open Spark Shell. This article is for beginners to get started with Spark Setup on Eclipse/Scala IDE and getting familiar with Spark terminologies in general - Hope you have read previous article on RDD basics , to get a basic understanding of Spark RDD. It happened to be difficult to find some ready to play with schema and data to load. For the remaining of this documentation we will focus on Scala examples for now. users can run a complex SQL query on top of an HBase table inside Spark, perform a table join against Dataframe, or integrate with Spark Streaming to implement a more complicated system. If you're not comfortable with Scala, I recently wrote a Java developer's Scala cheat sheet (based on Programming in Scala SE book, by Martin Odersky, whose first edition is freely available online), which is basically a big reference card, where you can look up almost any Scala topic you come across. Hence, you may need to experiment with Scala and Spark instead. If you have flat files such as CSV and TSV, you can use Apache HBase bulk load CSV and TSV features to get the data into HBase tables. This HBase tutorial will provide a few pointers of using Spark with Hbase and several easy working examples of running Spark programs on HBase tables using Scala language. Compare this Spark output with that of the Greenplum Database \d faa. It is the right time to start your career in Apache Spark as it is trending in market. It produces some random words and then stores them in an HBase table, creating the table if necessary. Other Spark example code does the following: We use a Scala case class to define the sensor schema. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy. The example in Scala of reading data saved in hbase by Spark and the example of converter for python @GenTang / ( 3) The example in scala transfers the data saved in hbase into Buffer[String] which contains row, column:cell, timestamp, value, type. We will create a small spark application which will load the local data file and show the output. HBase Tutorial. Tutorial: Create a Scala Maven application for Apache Spark in HDInsight using IntelliJ. You’ll also get an introduction to running machine learning algorithms and working with streaming data. Normal Load using org. HQL, Pig Latin, HDFS, Flume and HBase adds to his forte. Spark is built on the concept of distributed datasets, which contain arbitrary Java or Python objects. 3 versions due to PHOENIX-2040 being missed (here is the internal jira). This seems quite tedious since a simple program to load a CSV file working on the spark-shell doesn't even compile in Intellij. Have you tried on HDP 2. Resilient Distributed Datasets (RDD) is a fundamental data structure of Spark. Apache Spark is a lightning-fast cluster computing designed for fast computation. scala and python converter HBaseConverters. I found numerous samples in internet which asks to create a DSTREAM to get the data from HDFS files and all. I have kept the content simple to get you started. Apache Spark is an open-source parallel processing framework that supports in-memory processing to boost the performance of big-data analytic applications. Full stack engineers who are conversant with Apache Spark, Scala, Kafka & HBase. In this lab you will discover how to compile and deploy a Spark Streaming application and then use Impala to query the data it writes to HBase. I found numerous samples in internet which asks to create a DSTREAM to get the data from HDFS files and all. Assume that we have a set of XML files which has user information like first name, last name and etc. In this blog, we will see how to access and query HBase tables using Apache Spark. I read "SPARK-ON-HBASE: DATAFRAME BASED HBASE CONNECTOR" ( Github) and saw the parameters for running spark-shell. Shaded Protocol, Apache HBase - Spark, Apache HBase Patched Scala Compiler, Scala. 3 versions due to PHOENIX-2040 being missed (here is the internal jira). Hence, you may need to experiment with Scala and Spark instead. I will share my day-to-day experiences with technology ranging from java/c/c++/scala to spark, hbase and other big data technologies. FusionInsight HD V100R002C70, FusionInsight HD V100R002C80. Again, I'll fill in all the details of this Scala code in later lectures. Spark SQL Tutorial - Understanding Spark SQL With Examples Last updated on May 22,2019 125. How to access HBase from spark-shell using YARN as the master on CDH 5. broadcast and then use value method to access the shared value. Scala loop a file. Spark joins are used for datasets. Please see attached if you want to have a quick start. Welcome to the fifth chapter of the Apache Spark and Scala tutorial (part of the Apache Spark and Scala course). HBase provides random, realtime read/write access to the Bigdata. In this Apache HBase Tutorial, we will study a NoSQL DataBase. These examples are extracted from open source projects. scala return only the value of first column in the result. Note: I originally wrote this article many years ago using Apache Spark 0. This topic contains Scala user-defined function (UDF) examples. In this lab you will discover how to compile and deploy a Spark Streaming application and then use Impala to query the data it writes to HBase. Inserting records in HBase table is easy and all you need is to use Put command for the same. Scala compiles down to byte-code. Scala Variables, variable in Scala, how many types of variables in Scala, Scala tutorial, Scala variable tutorial, what is different between val and var in Scala, val vs var in Scala, Scala variables,Scala Tutorial for beginners, scala variable scope. The Spark Scala Solution. Use Apache Spark to read and write Apache HBase data. To toggle HBase management of ZooKeeper,. Hbase, Spark and HDFS - Setup and a Sample Application Apache Spark is a framework where the hype is largely justified. Again, I'll fill in all the details of this Scala code in later lectures. Spark provides an interface for programming entire clusters with implicit data parallelism and fault-tolerance. OK, I Understand. In this blog, we will be discussing the operations on Apache Spark RDD using Scala programming language. You can use Spark to call HBase APIs to operate HBase tables. Apache Spark is a unified analytics engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing. Hadoop Tutorial. Join (): In Spark simple join is used for the inner join between two RDDs. Please see attached if you want to have a quick start. I have kept the content simple to get you started. Spark is best known for its ability to cache large datasets in memory between intermediate calculations. users can run a complex SQL query on top of an HBase table inside Spark, perform a table join against Dataframe, or integrate with Spark Streaming to implement a more complicated system. Tutorial series on Hadoop, with free downloadable VM for easy testing of code. This has been a very useful exercise and we would like to share the examples with everyone. Efficient bulk load of HBase using Spark. Ayush is a Software Consultant, with experience of more than 1 year. I could able to read the data. 0, and Elasticsearch 6. Through this Apache Spark tutorial, you will get to know the Spark architecture and its components like Spark Core, Spark Programming, Spark SQL, Spark Streaming, MLlib, and GraphX. This code will read the HBase snapshot, filter records based on rowkey range (80001 to 90000) and based on a timestamp threshold (which is set in the props file), then write the results back to HDFS in HBase format (HFiles/KeyValue). 06/26/2019; 6 minutes to read +3; In this article. newAPIHadoopRDD is the API available in Spark to create RDD on hbase, configurations need to passed as shown below. I think that you realize that there’s a lot more public code in Java that works seamlessly with HBase because HBase was created in Java. We assure that you will not find any problem in this Scala tutorial. To help you learn Scala from scratch, I have created this comprehensive guide. You will get in-depth knowledge on Apache Spark and the Spark Ecosystem, which includes Spark DataFrames, Spark SQL, Spark MLlib and Spark Streaming. In this article, we will check create tables using HBase shell commands and examples. Spark reduce operation is an action kind of operation and it triggers a full DAG execution for all pipelined lazy instructions. Apache Spark DataFrame hbase realtime scala scala program usecase. How to use Scala on Spark to load data into Hbase/MapRDB -- normal load or bulk load. users can run a complex SQL query on top of an HBase table inside Spark, perform a table join against Dataframe, or integrate with Spark Streaming to implement a more complicated system. Use Apache Spark to read and write Apache HBase data. The following notebook shows this by using the Spark Cassandra connector from Scala to write the key-value output of an aggregation query to Cassandra. 0) + Spark Configuration on CDH5; Graphite's Dashboard JS to set auto-hide navBar on dashboard view 自动隐藏Dashboard视图中的导航栏. kafka-console producer writes to a one or more topics and Spark streaming consumer consumes the messages from the topic and writes the count of each word to an HBase table. This project allows to connect Apache Spark to HBase. 6 points to compare Python and Scala for Data Science using Apache Spark Posted on January 28, 2016 by Gianmario Apache Spark is a distributed computation framework that simplifies and speeds-up the data crunching and analytics workflow for data scientists and engineers working over large datasets. In this blog, we will see how to access and query HBase tables using Apache Spark. X version) DataFrame rows to HBase table using hbase-spark connector and Datasource "org. In Spark 1. HBaseContextが含まれるjarファイルの入手元、jarファイル名を教えて頂けないでしょうか。. You will get in-depth knowledge on Apache Spark and the Spark Ecosystem, which includes Spark DataFrames, Spark SQL, Spark MLlib and Spark Streaming. Head to Head differences between Hive vs HBase (Infographics) Below is the Top 8 Difference between Hive vs HBase. Applications that run on PNDA are packaged as tar. Other Spark example code does the following: We use a Scala case class to define the sensor schema. Unlike the earlier examples with the Spark shell, which initializes its own SparkSession, we initialize a SparkSession as part of the program. In this tutorial, you learn how to create an Apache Spark application written in Scala using Apache Maven with IntelliJ IDEA. Requirement You have two table named as A and B. Among these languages, Scala and Python have intuitive shells for Spark. Spark reduce operation is an action kind of operation and it triggers a full DAG execution for all pipelined lazy instructions. GitHub Gist: instantly share code, notes, and snippets. 1 Case 5: Example of Spark on HBase 1. Originally developed at the University of California, Berkeley's AMPLab, the Spark codebase was later donated to the Apache Software Foundation, which has maintained it since. 4 Obtaining Spark. To understand this article, users need to have knowledge of hbase, spark, java and scala. Hbase, Spark and HDFS - Setup and a Sample Application Apache Spark is a framework where the hype is largely justified. Comparing Hive with HBase is like comparing Google with Facebook - although they compete over the same turf (our private information), they don’t provide the same functionality. HBase is a Hadoop project which is Open Source, distributed Hadoop database which has its genesis in the Google'sBigtable. Head to Head differences between Hive vs HBase (Infographics) Below is the Top 8 Difference between Hive vs HBase. Open Spark Shell. 11, spar-sql_2. See the foreachBatch documentation for details. A pioneer in Corporate training and consultancy, Geoinsyssoft has trained / leveraged over 10,000 students, cluster of Corporate and IT Professionals with the best-in-class training processes, Geoinsyssoft enables customers to reduce costs, sharpen their business focus and obtain quantifiable results. Put(For Hbase and MapRDB) This way is to use Put object to load data one by one. FusionInsight HD V100R002C70, FusionInsight HD V100R002C80. For whom likes Jupyter, we'll see how we can use it with PySpark. How to build a Spark fat jar in Scala and submit a job Are you looking for a ready-to-use solution to submit a job in Spark? These are short instructions about how to start creating a Spark Scala project, in order to build a fat jar that can be executed in a Spark environment. From the command line, let's open the spark shell with spark-shell. Once parallelized, it becomes a Spark native. I found numerous samples in internet which asks to create a DSTREAM to get the data from HDFS files and all. Join (): In Spark simple join is used for the inner join between two RDDs. For example, 2. To manage and access your data with SQL, HSpark connects to Spark and enables Spark SQL commands to be executed against an HBase data store. In this article, I will introduce how to use hbase-spark module in the Java or Scala client program. , in our case default values for local server work. Easily run popular open source frameworks—including Apache Hadoop, Spark, and Kafka—using Azure HDInsight, a cost-effective, enterprise-grade service for open source analytics. I am trying to identify a solution to read data from HBASE table using spark streaming and write the data to another HBASE table. There are no primitive types in Scala, Everything is an object in Scala. We will create the […]. Originally developed at the University of California, Berkeley's AMPLab, the Spark codebase was later donated to the Apache Software Foundation, which has maintained it since. I could able to read the data. Efficient bulk load of HBase using Spark. spark_hbase. Spark on the other hand is a novel approach to deal with large quantities of data with complex, arbitrary computations on it. Learn Apache Spark Tutorials and know how to filter DataFrame based on keys in Scala List using Spark UDF with code snippets example. In this tutorial, you learn how to create an Apache Spark application written in Scala using Apache Maven with IntelliJ IDEA. DefaultSource does not allow create table as select looking for sample snippet. Spark is built on the concept of distributed datasets, which contain arbitrary Java or Python objects. Using Spark and Kafka This example, written in Scala, uses Apache Spark in conjunction with the Apache Kafka message bus to stream data from Spark to HBase. The following code examples show how to use org. Spark can read/write to any storage system / format that has a plugin for Hadoop! - Examples: HDFS, S3, HBase, Cassandra, Avro, SequenceFile - Reuses Hadoop's InputFormat and OutputFormat APIs. Click "Build", select current date as the build end date. The following code snippets are used as an example. Shaded Protocol, Apache HBase - Spark, Apache HBase Patched Scala Compiler, Scala. Spark has their own example about integrating HBase and Spark in scala HBaseTest. Apache Spark Examples. The example was provided in SPARK-944. Effortlessly process massive amounts of data and get all the benefits of the broad open source ecosystem with the global scale of Azure. {HBaseAdmin, Result} import org. I will create a maven project from scratch. On Scala, HBase, and MapReduce July 26, 2014 July 26, 2014 Posted in Analytics , Code I've been tinkering in Scala for years now, and I know my way around Hadoop - and more specifically, HBase - just fine. I have seen couple of good example at HBase Github. To run this example, you need to install the appropriate Cassandra Spark connector for your Spark version as a Maven library. It was originally developed in 2009 in UC Berkeley's AMPLab, and open. 1 Case 5: Example of Spark on HBase 1. Spark uses Java's reflection API to figure out the fields and build the schema. Hence, you may need to experiment with Scala and Spark instead. Authors of examples: Matthias Langer and Zhen He Emails addresses: m. What we want is to loop the file, and process one line each time. This article shows a sample code to load data into Hbase or MapRDB(M7) using Scala on Spark. Spark can read/write to any storage system / format that has a plugin for Hadoop! - Examples: HDFS, S3, HBase, Cassandra, Avro, SequenceFile - Reuses Hadoop’s InputFormat and OutputFormat APIs. All functionality between Spark and HBase will be supported both in Scala and in Java, with the exception of SparkSQL which will support any language that is supported by Spark. 6 points to compare Python and Scala for Data Science using Apache Spark Posted on January 28, 2016 by Gianmario Apache Spark is a distributed computation framework that simplifies and speeds-up the data crunching and analytics workflow for data scientists and engineers working over large datasets. The Spark Scala Solution. But if there is any mistake, please post the problem in contact form. 4? Not sure if its related but there was an issues with phoenix-spark connector in previous minor versions of 2. With Spark Shell with Scala, we can execute different commands of RDD transformation /action to process the data,is explained below. Spark provides the shell in two programming languages : Scala and Python. {HBaseAdmin, Result} import org. This feature is not available right now. Example 2-4. This post will help you get started using Apache Spark DataFrames with Scala on the MapR Sandbox. You want to add deep learning functionalities (either training or prediction) to your Big Data (Spark) programs and/or workflow. This was all about How to Insert Data in HBase table. In Spark 1. Spark uses Java's reflection API to figure out the fields and build the schema. Assume that we have a set of XML files which has user information like first name, last name and etc. HBase Tutorial. 0 GA (hadoop 2. 4 and Hive 1. Note that the Greenplum Database data type names differ from those of Spark. This article shows a sample code to load data into Hbase or MapRDB(M7) using Scala on Spark. Spark can work with multiple formats, including HBase tables. Originally developed at the University of California, Berkeley's AMPLab, the Spark codebase was later donated to the Apache Software Foundation, which has maintained it since. Spark can work on data present in multiple sources like a local filesystem, HDFS, Cassandra, Hbase, MongoDB etc. We want to store every single event in HBase as it streams in. Scala on Spark cheatsheet Example 2: Left Outer Join scala> kv This article shows a sample code to load data into Hbase or MapRDB(M7) using Scala on Spark. RDD is simply a distributed collection of elements Resilient. For this tutorial we'll be using Scala, but Spark also supports development with Java, and Python. rightOuterJoin() 3. More than 2. 2 How to access HBase from spark-shell using YARN as the master on CDH 5. Azure HDInsight offers a fully managed Spark service with many benefits. In this tutorial, we'll learn about Spark and then we'll install it. Hopefully the content below is still useful, but I wanted to warn you up front that it is old. 4, expected in June, will add R language support too. In the following tutorial modules, you will learn the basics of creating Spark jobs, loading data, and working with data. Hadoop Tutorial. In this lab you will discover how to compile and deploy a Spark Streaming application and then use Impala to query the data it writes to HBase. For example in the car data set from UCI Machine Learning. Spark provides an interface for programming entire clusters with implicit data parallelism and fault-tolerance. The Scala and Java code was originally developed for a Cloudera tutorial written by Sandy Ryza. Open Spark Shell. Assume that we have a set of XML files which has user information like first name, last name and etc. Apache Kafka + Spark Streaming + HBase Production Real Time Use Case Illustration PayPal merchant ecosystem using Apache Spark, Hive, Druid, and HBase Swift Programming Tutorial for. Spark uses Java's reflection API to figure out the fields and build the schema. It is written in Java and currently used by Google, Facebook, LinkedIn, Yahoo, Twitter etc. Unfortunately, I could not get the HBase Python examples included with Spark to work. and you want to perform all types of join in spark using scala. Spark provides the shell in two programming languages : Scala and Python. I am trying to identify a solution to read data from HBASE table using spark streaming and write the data to another HBASE table. It was built on top of Hadoop MapReduce and it extends the MapReduce model to efficiently use more types of computations which includes Interactive Queries and Stream Processing. Applicable Versions. Our HBase tutorial is designed for beginners and professionals. 11 !scala-2.