You can use the Hive Warehouse Connector (HWC) API to access any type of table in the Hive catalog from Spark. Workflow change: You must use the Hive Warehouse Connector API to access any managed table in the Hive catalog from Spark. 14 version or not. SQL-like queries (HiveQL), which are implicitly converted into MapReduce or Tez, or Spark jobs. For example if an import that creates and populates a Hive table is failing, you can break it down into two steps - first for doing the import alone, and the second to create a Hive table without the import using the create-hive-table tool. Spark introduced dataframes in version 1. Importing 'Row' class into the Spark Shell. This is part 1 of a 2 part series for how to update Hive Tables the easy way Historically, keeping data up-to-date in Apache Hive required custom application development that is complex, non-performant […]. All the columns have the string, character varying data-type for Hive, Impala, Spark and Drill. This section describes how to use the INSERT INTO statement to insert or overwrite rows in nested MapR Database JSON tables, using the Hive connector. So, Spark shows incorrect result for that table. Using Amazon EMR version 5. By default, Hive stores metadata in an embedded Apache Derby database, and other client/server databases like MySQL can optionally be used. x can be downloaded. We can call this Schema RDD as Data Frame. Further Reading. Recently, we felt Spark had matured to the point where we could compare it with Hive for a number of batch-processing use cases. 2 on Amazon EMR release 5. When you use SparkSQL, standard Spark APIs access tables in the Spark catalog. If you already have a Hive metastore, such as the one used by Azure HDInsight, you can use Spark SQL to query the tables the same way you do it in Hive with the advantage to have a centralized metastore to manage your table schemas from both Databricks and HDInsight. Another question,. Now, we will discuss how we can efficiently import data from MySQL to Hive using Sqoop. Prerequisites. Minimum requisite to perform Hive CRUD using ACID operations is: 1. Generally, you cannot be update or overwrite Hive table without deleting the whole file and writing it again with the updated data set. 0 provides builtin support for Hive features including the ability to write queries using HiveQL, access to Hive UDFs, and the ability to read data from Hive tables. 03 Spark SQL - Create Hive Tables Update Data in Hive Table. In this article explains Hive create table command and examples to create table in Hive command line interface. We use the Metastore app and its create table wizard. An important aspect of unification that our users have consistently requested is the ability to more easily import data stored in external sources, such as Apache Hive. I have used this in 9. It’s also possible to execute SQL queries directly against tables within a Spark cluster. I had to use sbt or Maven to build a project for this purpose but it works. You will also learn on how to load data into created Hive table. Let’s say you have a table. Execute a Hive SELECT query and return a DataFrame. Because Spark uses the underlying Hive infrastructure, with Spark SQL you write DDL statements, DML statements, and queries using the HiveQL syntax. No, it is not suitable for OLTP system since it does not offer insert and update at the row level. UPDATE kudu_table SET c3 = upper(c3), c4 = FALSE, c5 = 0 WHERE c6 = TRUE; The following examples show how to perform an update using the FROM keyword with a join clause:. Note that this guide is quite old (it was written when Hive was at version 0. Sqoop provides a simple command line, we can fetch data from the different database through sqoop. When Hive tries to “INSERT OVERWRITE” to a partition of an external table under existing directory, depending on whether the partition definition already exists in the metastore or not, Hive will behave differently:. It is suitable for accessing and analyzing data in Hadoop using SQL syntax. when I create Hive Table using Spark saveAsTable, I see spark registering Table with its own Custom Serde and Is recognizing the format and I am able to push down filters. There is also a setup-mysql. add columns to hive/parquet table how else can I update the columns or make sure that spark take the. Before we move ahead you can go through the below link blogs to gain more knowledge on Hive and its working. If the destination table name already exists, an exception is thrown. Recommended Books. Import Data to Hive from Oracle Database 5. If you ever come across null values while reading valid parquet files using Spark application, most likely you missed the following property in your spark job. Tag - update hive table using spark. Install Tableau DevBuild 8. Step 3: Create temporary Hive Table and Load data. 14 version or not. This allows you to query the table, insert data into the table, and even join the table with other Hive or Spark SQL tables. Beginners Guide For Hive Perform Word Count Job Using Hive Pokemon Data Analysis Using Hive Connect Tableau Hive. What is HQL? Hive defines a simple SQL-like query language to querying and managing large datasets called Hive-QL ( HQL ). In this video lecture we see how to read a csv file and write the data into Hive table. Creates a new Hive table using the name provided. This release also includes two new performance optimizations that improve Spark performance up to 3x* over EMR 5. Create a table pointing to your file in Object Storage and retrieve using Hive QL. Starting with MEP 6. Now, you have a file in Hdfs, you just need to create an external table on top of it. but let’s keep the transactional table for any other posts. To load the data from local to Hive use the following command in NEW terminal:. You should see this: This example shows the most basic ways to add data into a Hive table using INSERT, UPDATE and DELETE commands. This post will help you get started using Apache Spark DataFrames with Scala on the MapR Sandbox. How was this patch tested? It's difficult to add a unit test. It is not mandatory to create a metastore in Spark SQL but it is mandatory to create a Hive metastore. Those are Parquet file, JSON document, HIVE. Note that this is different from the Hive behavior. Spark Connection. For further information on Spark SQL, see the Apache Spark Spark SQL, DataFrames, and Datasets Guide. RStudio Server is installed on the master node and orchestrates the analysis in spark. Then it creates MapReduce jobs in Java. Click through for a tutorial on using the new MongoDB Connector for Apache Spark. 2: Hive Tables. Second question: How to update Hive table from Spark ? As of now, Hive is not a best fit for record level updates. Plus it moves programmers toward using a common database. Hello all, welcome to another article on Apache Hive. That means instead of Hive storing data in Hadoop it stores it in Spark. still does not work due to HIVE-4847 is not fixed yet. We have created table, now let us INSERT some records to the tables and check how update works in Hive with transaction tables. In this tutorial, we will cover using Spark SQL with a mySQL database. SparkSession in Spark 2. You need to enter the Hive query statement you want to use to select the data to be used. If the destination table name already exists, an exception is thrown. Data are downloaded from the web and stored in Hive tables on HDFS across multiple worker nodes. Spark SQL is a Spark module for structured data processing. So the data now is stored in data/weather folder inside hive. State of art optimization and code generation through the Spark SQL Catalyst optimizer (tree transformation framework). File format should be in ORC file format with TBLPROPERTIES(‘transactional’=’true’). Beginners Guide For Hive Perform Word Count Job Using Hive Pokemon Data Analysis Using Hive Connect Tableau Hive. I then found out that Spark 2. Workflow change: You must use the Hive Warehouse Connector API to access any managed table in the Hive catalog from Spark. Users who are comfortable with SQL, Hive is mainly targeted towards them. oracle,hadoop,hive,sqoop. In addition, you will learn about Sqoop Export to migrate data effectively, and about Apache Flume to ingest data. @ Kalyan @: How To Stream JSON Data Into Hive Using Apache Flume, hadoop training in hyderabad, spark training in hyderabad, big data training in hyderabad, kalyan hadoop, kalyan spark, kalyan hadoop training, kalyan spark training, best hadoop training in hyderabad, best spark training in hyderabad, orien it hadoop training, orien it spark. Some good alternative for simplifying the data management or access is to use Apache Pig or Hive. Join HdfsTutorial. (works fine as per requ. Managing Slowly Changing Dimensions. 03 Spark SQL - Create Hive Tables Update Data in Hive Table. Which allows to have ACID properties for a particular hive table and allows to delete and update. However, the Data Sources for Spark SQL is different. Delta Lake enables you to make changes to a table schema that can be applied automatically, without the need for cumbersome DDL. 10) and might not apply as-is to recent Hive releases. This will really be useful. Using the Hive query language (HiveQL), which is very similar to SQL, queries are converted into a series of jobs that execute on a Hadoop cluster through MapReduce or Apache Spark. updateTableStats -> Hive. All the columns have the string, character varying data-type for Hive, Impala, Spark and Drill. Under the hood, Redshift Data Source for Spark will first create the table in Redshift using JDBC. Using Spark to read a Hive Table with SQL and giving analyzed info about it. File format must be in ORC file format with TBLPROPERTIES('transactional'='true') 3. As such, incremental models are implemented differently than usual in this plugin. sbt by adding Library dependency. In order to check the connection between Spark SQL and Hive metastore, the verification of the list of Hive databases and tables using Hive prompt could be done. Here is an example statement to create a table using sequence File:. Using HBase and Impala to Add Update and Delete Capability to Hive DW Tables, and Improve Query Response Times 19 May 2015 on Big Data, Technical, obiee, Oracle BI Suite EE, hadoop, Hive, Impala, hbase, DW Offloading. Like Hadoop, Hive has evolved to encompass more than just MapReduce. Depending on the Talend solution you are using, this component can be used in one, some or. Tip 1: Partitioning Hive Tables Hive is a powerful tool to perform queries on large data sets and it is particularly good at queries that require full table scans. Azure HDInsight offers a fully managed Spark service with many benefits. Static columns are mapped to different columns in Spark SQL and require special handling. Launching Xcode Launching Visual Studio Latest commit 6ab Feb 2, Update When I first created this project in the Hive project did not produce a "standalone" jar that reliably contained all required dependencies to successfully create a JDBC connection. As such, incremental models are implemented differently than usual in this plugin. Managing Slowly Changing Dimensions. Moreover, We get more information of the structure of data by using SQL. A library to read/write DataFrames and Streaming DataFrames to/from Apache Hive™ using LLAP. Spark introduced dataframes in version 1. Using Amazon EMR version 5. CREATE TABLE mytable ( name string, city string, employee_id int ) PARTITIONED BY (year STRING, month STRING, day STRING) CLUSTERED BY (employee_id) INTO 256 BUCKETS. Hello all, welcome to another article on Apache Hive. When you use SparkSQL, standard Spark APIs access tables in the Spark catalog. Second question: How to update Hive table from Spark ? As of now, Hive is not a best fit for record level updates. This output location can then be moved over to a different Hadoop or Hive instance and imported from there with the IMPORT command. The UPDATE STATISTICS command updates the statistics collected on a table. Creating DataFrames. Run below script in hive CLI. In BI world delta load/incremental load to update the existing record and Inserting new record is very common process. However, beginning with Spark 2. So Hive jobs will run much faster there. To get a quick peek at Hudi’s capabilities, we have put together a demo video that showcases this on a docker based setup with all dependent systems running locally. 2 for examples mentioned below. Those are Parquet file, JSON document, HIVE. and I believe this has to do something with it. At Spark Summit 2017, we described our framework to migrate production Hive workload to Spark with minimal user intervention. Using HBase and Impala to Add Update and Delete Capability to Hive DW Tables, and Improve Query Response Times 19 May 2015 on Big Data, Technical, obiee, Oracle BI Suite EE, hadoop, Hive, Impala, hbase, DW Offloading. there are two solution for you to do that: 1. This would also facilitate the pain point of incremental updates on fast moving/changing data loads. Many users can simultaneously query the data using Hive-QL. Hive Most Asked Interview Questions With Answers – Part I,Spark Interview Questions Part-1,Hive Scenario Based Interview Questions with Answers Apache Spark for Java Developers ! Get processing Big Data using RDDs, DataFrames, SparkSQL and Machine Learning – and real time streaming with Kafka!. To overcome this issue, we will send Hive table data to HBase that require update values. Follow the below steps: Step 1: Sample table in Hive. Hive ACID tables support UPDATE, DELETE, INSERT, MERGE query constructs with some limitations and we will talk about that too. Also, gives information on computations performed. This is a known issue only in Spark 2. The API supports reading and writing Hive tables from Spark. External Hive Metastore. Impala – HIVE integration gives an advantage to use either HIVE or Impala for processing or to create tables under single shared file system HDFS without any changes in the table definition. Minimum requisite to perform Hive CRUD using ACID operations is: 1. Process the data with Business Logic (If any) Stored in a hive partition table. Set Up a Hive Table to Run Hive Commands. The Spark master node connects to SQL Server or Azure SQL Database and loads data from a specific table or using a specific SQL query; The Spark master node distributes data to worker nodes for transformation. One of the most important pieces of Spark SQL's Hive support is interaction with Hive metastore, which enables Spark SQL to access metadata of Hive tables. there are two solution for you to do that: 1. Hive is a append only database and so update and delete is not supported on hive external and managed table. We can call this Schema RDD as Data Frame. You need to use the Spark Configuration tab in the Run view to define the connection to a given Spark cluster for the whole Job. When you issued HiveQL statements against the external table, the read and write operations were passed through to the DynamoDB table. Update and Delete on Hive table (Hive supports CRUD) In this blog we have a quick overview of how to use spark SQL and dataframes for common use cases in SQL. Spark insert / append a record to RDD / DataFrame ( S3 ) Posted on December 8, 2015 by Neil Rubens In many circumstances, one might want to add data to Spark; e. 2, and MEP 3. These solutions include updating Hive tables using the Update Strategy transformation, Update Strategy transformation with the MERGE statement, partition merge solution, and key-value stores. Its purpose is to relieve the developer from a significant amount of relational data persistence-related programming tasks. Kudu allows insert,delete,update on tables in collaboration with impala. col1 = 10' load the entire table or partition and process all the rows. 4, the UPDATE statement is supported with Hive MapR Database JSON tables. HDFS datasets in DSS are always true “HDFS datasets”. In addition, since the Job expects its dependent jar files for execution, one and only one file system related component from the Storage family is required in the same Job so that Spark can use this. Tables with partitions using different input formats: In Spark SQL, all table partitions need to have the same input format. This comprehensive guide introduces you to Apache Hive, Hadoop’s data warehouse infrastructure. Key Customer Benefits. Now if we try to re-insert the same data again, it will be appended to the previous data as shown below: Updating the Data in Hive Table UPDATE college set clg_id = 8. First, we would have to filter tweets which seem relevant like "earthquake" or "shaking". Note, as part of Spark 1. Now data is inserted but you need to remember one thing that each way of inserting data have it own merits. In this blog, we will be discussing the types of tables in Hive and the difference between them and how to create those tables and when to use those tables for a. The API supports reading and writing Hive tables from Spark. HDFS datasets in DSS are always true “HDFS datasets”. Spark integrates seamlessly with Hadoop and can process existing data. When you use SparkSQL, standard Spark APIs access tables in the Spark catalog. There are several ways to interact with Spark SQL including SQL and the Dataset API. You have now created a HIVE table from s3 data. Hive version 0. alterTable The PR update the logic to avoid repeating calculate table statistics. While some uncommon operations will need to be performed using Hive directly, most operations can be performed using Presto. In this video I have explained about how to read hive table data using the HiveContext which is a SQL execution engine. 2 for examples mentioned below. The behavior of DataGrip was unchanged. Load Text file into Hive Table Using Spark. No more Update/Delete/Merge may be executed against these tables since the start of Major compaction. add columns to hive/parquet table how else can I update the columns or make sure that spark take the. If a table is to be used in ACID writes (insert, update, delete) then the table property "transactional" must be set on that table. Apache Hive ALTER TABLE Command, Hive ALTER TABLE Command Syntax, Hive ALTER TABLE Command Examples, Rename Hive Table using ALTER TABLE Command, Add new column to Hive Table using ALTER TABLE Command, Change Hive Table Column name and Type using ALTER command, Add and Drop Partition using ALTER TABLE Command. Get prepared. This time we are having the same sample JSON data. Generally, you cannot be update or overwrite Hive table without deleting the whole file and writing it again with the updated data set. UPDATE kudu_table SET c3 = 'impossible' WHERE 1 = 0; -- Change the values of multiple columns in a single UPDATE statement. Which allows to have ACID properties for a particular hive table and allows to delete and update. We optimized the code a lot to make this process efficient. However, the Data Sources for Spark SQL is different. There are two approaches explained below with 'Employee' table example to store pig output into hive table. Moreover, We get more information of the structure of data by using SQL. It means that if a table is deleted the corresponding directory in HDFS or S3 will also be deleted. 2, and MEP 3. Yet many queries run on Hive have filtering where clauses limiting the data to be retrieved and processed, e. Using Hive with Existing Files on S3 Posted on September 30, 2010 April 26, 2019 by Kirk True One feature that Hive gets for free by virtue of being layered atop Hadoop is the S3 file system implementation. Users are not allowed to specify the location for Hive managed tables. The HBase app is an elegant way to visualize and search a lot of data. Below is the code that I have written to load the data. Data scientists often want to import data into Hive from existing text-based files exported from spreadsheets or databases. Add support for Hive String columns of more than 255 characters without truncation. You need to understand how to use HWC to access Spark tables from Hive in HDP 3. We could easily use Spark Streaming for that purpose as follows:. Hive ACID tables support UPDATE, DELETE, INSERT, MERGE query constructs with some limitations and we will talk about that too. AvroSerDe takes care of creating the appropriate Avro schema from the Hive table schema, a big win in terms of Avro. Update Data in Hive Table - Duration: Spark Tutorial - Data Sources. You will need to insert the IP address range of the Spark cluster that will be executing your application (as on line 9 and 12). Using the Hive query language (HiveQL), which is very similar to SQL, queries are converted into a series of jobs that execute on a Hadoop cluster through MapReduce or Apache Spark. or Hive tables. Note that for on-disk Hive * tables, a data directory is created for each partition corresponding to keys specified using * 'PARTITION BY'. You will learn about Spark Dataframes, Spark SQL and lot more in the last sections. 0, Hive offers another API for mutating (insert/update/delete) records into transactional tables using Hive’s ACID feature. So now you have geolocation and trucks files stored in HDFS as csv files. Use case: Feature preparation for entity ranking. 2 on Amazon EMR release 5. While inserting data from a dataframe to an existing Hive Table. Learn how to use Spark & Hive Tools for Visual Studio Code to create and submit Apache Hive batch jobs, interactive Hive queries, and PySpark scripts for Apache Spark. This tutorial will show how to use Spark and Spark SQL with Cassandra. Data Sources − Usually the Data source for spark-core is a text file, Avro file, etc. xml properties not exposed by the UI. scala file should be updated with the same improvement to match the behavior of Hive. You can see that once the table is defined, it can be queried using a simple HiveQL query. The EXPORT command exports the data of a table or partition, along with the metadata, into a specified output location. the sql ran successfully with no errors. 1) Explain the difference between Spark SQL and Hive. RStudio Server is installed on the master node and orchestrates the analysis in spark. Those are Parquet file, JSON document, HIVE. updateTableStats -> Hive. It is very important for. In the case of Hive we are operating on the Apache Hadoop data store. So the data now is stored in data/weather folder inside hive. Hive Bucketing and Partitioning. Row is used in mapping RDD Schema. 14 the have started a new feature called transactional. Which allows to have ACID properties for a particular hive table and allows to delete and update. Property kylin. Visual programming allows code-free big-data science, while scripting nodes allow detailed control when desired. So the data now is stored in data/weather folder inside hive. when receiving/processing records via Spark Streaming. When the export of all the data is successful, then it will write the data in the table. The default location of Hive table is overwritten by using LOCATION. sql file and how to execute the file using the shell script. Using HBase and Impala to Add Update and Delete Capability to Hive DW Tables, and Improve Query Response Times 19 May 2015 on Big Data, Technical, obiee, Oracle BI Suite EE, hadoop, Hive, Impala, hbase, DW Offloading. 3 and enriched dataframe API in 1. 14 and later versions. Does this imply that Hive on Spark (Hive 2 encourages Spark or TEZ) is going to have an issue with transactional tables? Besides this begs the question that we still run Hive on Spark 1. For managed tables, renaming a table moves the table location; for unmanaged (external) tables, renaming a table does not move the table location. We don't specify the partition column in --columns option as it get automatically added. Appendix: SparkSQL 1. Launching GitHub Desktop Go back. Because Hive has full control of managed tables, Hive can optimize these tables extensively. For example if an import that creates and populates a Hive table is failing, you can break it down into two steps - first for doing the import alone, and the second to create a Hive table without the import using the create-hive-table tool. X; Spark Hbase Connector; Cloud Storage with Spark; File Format and Compression. optimizations. However, initially it did not take advantage of the full power of ORC. Starting with MEP 6. add columns to hive/parquet table how else can I update the columns or make sure that spark take the. Metastore security ¶. In HDInsight, we use Azure SQL database as Hive Metastore. This section describes how to use the INSERT INTO statement to insert or overwrite rows in nested MapR Database JSON tables, using the Hive connector. From hive version 0. Impala – HIVE integration gives an advantage to use either HIVE or Impala for processing or to create tables under single shared file system HDFS without any changes in the table definition. An important aspect of unification that our users have consistently requested is the ability to more easily import data stored in external sources, such as Apache Hive. Using Amazon EMR version 5. On tables NOT receiving streaming updates, INSERT OVERWRITE will delete any existing data in the table and write the new rows. Add support for Hive String columns of more than 255 characters without truncation. The architecture prevents the typical issue of users accidentally trying to access Hive transactional tables directly from Spark, resulting in inconsistent results, duplicate data, or data corruption. Then register the dataframe as temptable using df. For the DB rename to work properly, we need to update three tables in the HMS DB. Spark SQL can query DSE Graph vertex and edge tables. Can be easily integrated with all Big Data tools and frameworks via Spark-Core. Now you can query from the temptable and insert in to hive table using sqlContext. 2 on Amazon EMR release 5. Some more configurations need to be done after the successful. We don't seem to make Hive work on Spark engine with a newer version of Spark. A Phoenix table is created through the CREATE TABLE command and can either be:. The following examples use Hive commands to perform operations such as exporting data to Amazon S3 or HDFS, importing data to DynamoDB, joining tables, querying tables, and more. In this blog, we illustrate how SAP HANA SDA access the Hive table stored in Hadoop using a simple example. Read operations. Spark, Scala & Hive Sql simple tests. Get prepared. Importing Data from Files into Hive Tables. Spark SQL: In Spark, we use Spark SQL for structured data processing. Hive Create Table statement is used to create table. [SPARK-5950][SQL] Enable inserting array into Hive table saved as Parquet using DataSource API #4729 viirya wants to merge 4 commits into apache : master from viirya : hive_parquet Conversation 35 Commits 4 Checks 0 Files changed. SELECT * WHERE state=’CA’. The conf/kylin_hive_conf. HiveAuthorizationProvider interface hive. Install Tableau DevBuild 8. Hive comes bundled with the Spark library as HiveContext, which inherits from SQLContext. For further information on Spark SQL, see the Apache Spark Spark SQL, DataFrames, and Datasets Guide. With a HiveContext, you can access Hive or Impala tables represented in the metastore database. cassandra,nosql,bigdata,cassandra-2. Hive version 0. The conf/kylin_hive_conf. The on-disk layout of Acid tables has changed with this release. Create, use, and drop an external table You use an external table, which is a table that Hive does not manage, to import data from a file on HDFS, or another file system, into Hive. In addition, ACID compliant transactions have been added so that users get a consistent view of data while reading and writing. In the remainder of this article, we describe our experiences and lessons learned while scaling Spark to replace one of our Hive workload. RDDs are a unit of compute and storage in Spark but lack any information about the structure of the data i. The new Spark DataFrames API is designed to make big data processing on tabular data easier. You need to use the Spark Configuration tab in the Run view to define the connection to a given Spark cluster for the whole Job. x can be downloaded. Get unlimited access to the best stories on Medium — and support. The first example simply defines a Spark SQL table from an Azure SQL DW table using the JDBC connection. update or delete using Hive Table from One Cluster to Another; spark. Like Apache Spark, GraphX initially started as a research project at UC Berkeley's AMPLab and Databricks, and was later donated to the Apache Software Foundation and the Spark project. In below example script if table movies already exists then Kudu backed table can be created as follows: CREATE TABLE movies_kudu PRIMARY KEY (`movieid`) PARTITION BY HASH(`movieid`) PARTITIONS 8 STORED AS KUDU AS SELECT movieId, title, genres FROM movies;. Such as, Java, Scala, Python and R. Working with Spark and Hive Part 1: Scenario - Spark as ETL tool Write to Parquet file using Spark Part 2: SparkSQL to query data from Hive Read Hive table data from Spark Create an External Table. At first, let's understand what is Spark? Basically, Apache Spark is a general-purpose & lightning fast cluster computing system. java Find file Copy path Dustin Koupal [MINOR][DOCS] Fix typo in Hive Examples 8129d59 Apr 6, 2017. This time we are having the same sample JSON data. Beginners Guide For Hive Perform Word Count Job Using Hive Pokemon Data Analysis Using Hive Connect Tableau Hive. Streaming Mutation API. Previously, Spark ignores that option. Hive supports extending the UDF set to handle use-cases not supported by built-in functions. The section Apache Hive introduces Hive, alongside external and managed tables; working with different files, and Parquet and Avro-and more. Starting from Spark 1. The resource manager, YARN, allocates resources for applications across the cluster. No more Update/Delete/Merge may be executed against these tables since the start of Major compaction. Support was added for timestamp , decimal , and char and varchar data types. Loading/Saving from/to HBase from Spark; Spark UDFs; Rename Database in Hive; Hive 2 Hive; Create a scala project using maven on intellij; Kafka 2 Kafka Using Flume; Help 4 Apache Project; Using spark with hive at Windows; Ambari Email Notification; Spark 2. An important aspect of unification that our users have consistently requested is the ability to more easily import data stored in external sources, such as Apache Hive. Run below script in hive CLI. Spark SQL doesn't support buckets yet.