Pyspark Create Hive Table


Make sure the hive-site. A dataframe in Spark is similar to a SQL table, an R dataframe, or a pandas dataframe. Dynamically defining tables is very useful for complex analytics and with multiple staging points. There are a few ways to read data into Spark as a dataframe. All the data types in Hive are classified into four t. You use the Hive Warehouse Connector API to access any managed Hive table from Spark. I am using Python2 for scripting and Spark 2. Hadoop has a data warehouse system, named Hive, that allows querying and analyzing of data. Pyspark Interview Questions and answers are prepared by 10+ years experienced industry experts. This is my code, with spark 2. Spark's primary data abstraction is an immutable distributed collection of items called a resilient distributed dataset (RDD). We cannot pass the Hive table name directly to Hive context sql method since it doesn't understand the Hive table name. Whether your business is early in its journey or well on its way to digital transformation, Google Cloud's solutions and technologies help chart a path to success. sql(“create table yellow_trip_data as select * from yellow_trip”) //create normal table 4. Create Spark DataFrame from RDD. Once the file is moved in HDFS, use Apache Hive to create a table and load the data into a Hive warehouse. 6: Used to parse the file and load into hive table; Here, using PySpark API to load and process text data into the hive. It will store the data frame into hive database bdp_db with the table name "jsonTest". Quickstart: Create Apache Spark cluster in Azure HDInsight using Azure portal. sql('CREATE DATABASE IF NOT EXISTS unit08lab1') hive. In addition, we can also use the saveAsTable function. You'll use this package to work with data about flights from Portland and Seattle. Let's start off by outlining a couple of concepts. In HDP3, I am trying to ingest DB and File copy using PySaprk. [Hive-user] Hive queries returning all NULL values. When a table is small, this integration can work well, but Hive on HBase will not perform well on large tables. All the columns in the table should space separated…. This chapter describes how to drop a table in Hive. Once you create a Hive table, defining the columns, rows, data types, etc. Some links, resources, or references may no longer be accurate. We are using new Column() in code below to indicate that no values have been aggregated yet. We can also use data in Hive tables with other data frames by first registering the data frames as temporary tables. To have a great development in Pyspark work, our page furnishes you with nitty-gritty data as Pyspark prospective employee meeting questions and answers. 0 the spark catalog and hive catalog are separated now. sql import functions as sqlfunc # Adding a column 'year' to the data frame for partitioning the hive table. For example, consider two partitioned hive tables a & b joined in a view: create table a (a_val string) partitioned by (ds string) stored as orc;. Configure PySpark driver to use Jupyter Notebook: running pyspark will automatically open a Jupyter Notebook. 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 […]. environ["JAVA_HOME"] = "C:\\PROGRA~1\\Java\\jdk1. 6: Used to parse the file and load into hive table; Here, using PySpark API to load and process text data into the hive. CreateOrReplaceTempView on spark Data Frame Often we might want to store the spark Data frame as the table and query it, to convert Data frame into temporary view that is available for only that spark session, we use registerTempTable or CreateOrReplaceTempView (Spark > = 2. Create a flume conf file using fastest channel, which write data in hive warehouse directory, in a table called flumeemployee (Create hive table as well tor given data). This effectively performs the "--hive-import" step of sqoop-import without running the preceeding imp. CREATE TABLE: CREATE TABLE: テーブルを作成する。 externalが付いていないと、Hiveが管理しているディレクトリー(本来はHDFS)内にファイルが作られる。 externalが付いていると、指定したディレクトリー(本来はHDFS)内にファイルが作られる。 create table test1( col1 string);. But as you are saying you have many columns in that data-frame so there are two options. To the Almighty, who guides me in every aspect of my life. Now, let’s create a temporary table from the tags dataset and then we will join it with movies and rating tables which are in Hive. Hive metastore Parquet table conversion. table1 = sqlContext. Hive comes bundled with the Spark library as HiveContext, which inherits from SQLContext. UDAF; Create Inner Class which implements UDAFEvaluator; Implement five methods init() – The init() method initalizes the evaluator and resets its internal state. Step 5: Verify the data in Hive. sql("select * from table1") table1. Dynamically defining tables is very useful for complex analytics and with multiple staging points. • Have used Python with the Spark Python API (PySpark) to create and analyze Spark DataFrames. My requirement is I need to create a Spark In-memory table (Not pushing hive table into memory) insert data into it and finally write that back to Hive table. Output Directory (HDFS): /smartbuy/webpage_files. To correct this, we need to tell spark to use hive for metadata. from pyspark. 5 (7,859 ratings) Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately. To load data from Terdata to Hive parquet tables , used Sqoop to load the data Then Created Hive tables where I used and Wrote Partitions, Bucketing concepts in Hive and designed both Managed and External tables in Hive for optimized performance. Simply put, an External Table is a table built directly on top of a folder within a data source. Also can help to access tables in the Hive MetaStore. Most of the databases like Netezza, Teradata, Oracle, even latest version of Apache Hive supports analytic or window functions. "How can I import a. This is what i included in the script. HDPCD:Spark using Python (pyspark) 4. When you drop a table from Hive Metastore, it removes the table/column data and their metadata. If the statement that is returned uses a simple CREATE TABLE command, copy the statement and replace CREATE TABLE with CREATE TABLE EXTERNAL. Since I have already hadoop distcp all my necessary files to GCP, I’m now ready to create the tables in hive to point to the GCP files. The following two examples query Hive tables using Spark SQL queries. I'm trying to save spark dataframe into hive table. Edge table must have 3 columns and columns must be called src, dst and relationship (based on my personal experience, PySpark is strict about the name of columns). Is it possible to create a table on spark using a select statement? I do the following import findspark findspark. These files can be accessed by Hive tables using a SerDe that is part of Copy to Hadoop. Load JSON Data into Hive Partitioned table using PySpark. Hive implements an HBase Storage Handler, which allows us to create external tables on top of HBase. Or you can use the spark-sql client instead of hive. Using PySpark allows us to perform preprocessing on Hadoop and take advantage of the parallel execution, along with the in-memory processing that Spark provides. collect() Enjoy!. Importing Data into Hive Tables Using Spark. serializers import BatchedSerializer. Idea here is to avoid the disk IO while writing into Target Hive table. I was working on one of the task to transform Oracle stored procedure to pyspark application. Create DataFrame from list of tuples using Pyspark In this post I am going to explain creating a DataFrame from list of tuples in PySpark. Building a unified platform for big data analytics has long been the vision of Apache Spark, allowing a single program to perform ETL, MapReduce, and complex analytics. You need to understand the basic structure of Hive internal and external tables. 2 When I execute the show tables; query I get the. CREATE TABLE weather (wban INT, date STRING, precip INT) ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' LOCATION ' /hive/data/weather'; ROW FORMAT should have delimiters used to terminate the fields and lines like in the above example the fields are terminated with comma (","). Any query you make, table that you create, data that you copy persists from query to query. So far we have seen running Spark SQL queries on RDDs. The conventions of creating a table in HIVE is quite similar to creating a table using SQL. For Hive there exists such a possibility with the Hive Server…. Sqoop Architecture Sqoop provides command line interface to the end users. Install Windows Server 2012R2 using Virtualbox VHD Upgrade MySQL 5. It's fairly simple to work with Databases and Tables in Azure Databricks. Hive and Presto Clusters with Jupyter on AWS, Azure, and Oracle October 10, 2017 by Mikhail Stolpner and Qubole Updated January 15th, 2019 Jupyter™ Notebooks is one of the most popular IDE of choice among Python users. In HDP3, I am trying to ingest DB and File copy using PySaprk. def _create_from_pandas_with_arrow (self, pdf, schema, timezone): """ Create a DataFrame from a given pandas. In python, you can create your own iterator from list, tuple. Lets create DataFrame with sample data Employee. When a table is small, this integration can work well, but Hive on HBase will not perform well on large tables. 0 and later, Spark and Hive use independent catalogs for accessing SparkSQL or Hive tables on the same or different platforms. In short: I have a working hive on hdp3, which I cannot reach from pyspark, running under yarn (on the same hdp). In Hive, the database is considered as a catalog or namespace of tables. Hive Tables describes the detailed steps. pyspark --packages com. As we know, HBase is a column-oriented database like RDBS and so table creation in HBase is completely different from what we were doing in MySQL or SQL Server. NET for Apache Spark v0. Here is what I get when I run the simple command from pyspark in Spark 2. I use scala. In HDP3, I am trying to ingest DB and File copy using PySaprk. sql("create table yellow_trip_data as select * from yellow_trip") //create normal table 4. Once, we have downloaded and copied the winutils. Step 1 - Loaded the data from hive table into another table as follows DROP TABLE IF EXISTS TestHiveTableCSV; CREATE TABLE TestHiveTableCSV ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' LINES TERMINATED BY ' ' AS SELECT Column List FROM TestHiveTable; Step 2 - Copied the blob from hive warehouse to the new location with appropriate extension. init() import pyspark from pyspark. 7, Cloudera has added support for Hive-on-Spark. RDDs are one of the foundational data structures for using PySpark so many of the functions in the API return RDDs. Spark has API in Pyspark and Sparklyr, I choose Pyspark here, because Sparklyr API is very similar to Tidyverse. Once done with step 3. Such as, Java, Scala, Python and R. Congratulations, you are no longer a newbie to DataFrames. I hope you guys got an idea of what PySpark DataFrame is, why is it used in the industry and its features in this PySpark DataFrame tutorial. From Spark 2. Read rendered documentation, see the history of any file, and collaborate with contributors on projects across GitHub. GitHub makes it easy to scale back on context switching. Create Table Statement. A table created by Hive resides in the Hive catalog. In short: I have a working hive on hdp3, which I cannot reach from pyspark, running under yarn (on the same hdp). types import *. Hive/Parquet Schema. Now let's create two hive table A and B for both the files,using below commands:-hive table creation. 06/12/2019; 6 minutes to read +2; In this article. Quickstart: Create Apache Spark cluster in Azure HDInsight using Azure portal. 0 was just published on 2019-04-25 on GitHub. Support is currently available for spark-shell, pyspark, and spark-submit. DBFS Click Create Table in Notebook. then you can follow the following steps:. Create table on weather data. Use Hive to create Tableau Visualizations One metric we want to create is a ratio of the number of first person plural words (we, us, our, ours, ourselves) divided by the sum of first person singular and plural words (we, us, our, ours, ourselves, I, me, my, myself, mine). Pankaj K October 29, 2019 October 29, 2019 No Comments on How to use Hive Warehouse Connector in HDP 3. It is one of the very first objects you create while developing a Spark SQL application. 0, you can easily read data from Hive data warehouse and also write/append new data to Hive tables. Create a SparkSession with Hive supported. (works fine as per requ. sql(“DROP TABLE IF EXISTS csmessages_hive_table”) spark. To write and execute a Hive script, we need to install Cloudera distribution for Hadoop CDH4. Scala/Java usage: Locate the hive-warehouse-connector-assembly jar. Step 6 – Create hive temp folder. Such as, Java, Scala, Python and R. the table in the Hive metastore automatically inherits the schema, partitioning, and table properties of the existing data. PySpark/Hive: how to CREATE TABLE with LazySimpleSerDe to convert boolean 't/'f'? I create a Hive DB and a temp Hive table and then SELECT * from it, like this:. sql import HiveContext hive_context = HiveContext(sc) bank = hive_context. This PySpark SQL cheat sheet covers the basics of working with the Apache Spark DataFrames in Python: from initializing the SparkSession to creating DataFrames, inspecting the data, handling duplicate values, querying, adding, updating or removing columns, grouping, filtering or sorting data. In this post, we will see how to replace nulls in a DataFrame with Python and Scala. To correct this, we need to tell spark to use hive for metadata. Support Questions to create a keyProvider !! from pyspark. serializers import BatchedSerializer. It is conceptually equivalent to a table in a relational database or a data frame in R/Python, but with richer optimizations under the hood. In this video lecture we see how to read a csv file and write the data into Hive table. Hive has this wonderful feature of partitioning — a way of dividing a table into related parts based on the values of certain columns. sql('USE unit08lab1') Now we take our existing DataFrame ufo_dataframe and register it in Hive as a table. Let's start off by outlining a couple of concepts. Smita Rani Pathak. In addition to the basic SQLContext, you can also create a HiveContext, which provides a superset of the functionality provided by the basic SQLContext. Or you can use the spark-sql client instead of hive. Also can help to access tables in the Hive MetaStore. Transactional Tables: Hive supports single-table transactions. Hi Everyone, I have a basic question. Learn how to use the Azure HDInsight Tools for Visual Studio Code (VSCode) to create and submit Hive batch jobs, interactive Hive queries, PySpark batch, and PySpark interactive scripts. In order to avoid hive bugs, we need to create an empty directory at “C:\tmp\hive“. exe at the desired path and have created the required hive folder, we need to give appropriate permissions to the winutils. Dataframe basics for PySpark. If source is not specified, the default data source configured by spark. Some links, resources, or references may no longer be accurate. In Hive, the database is considered as a catalog or namespace of tables. OK, I Understand. partitiontest1(val string) partitioned by (year int)") "nonstrict"を使わないとSparkException: Dynamic partition strict mode requires at least one static partition column. sql(“CREATE TABLE csmessages_hive_table ( recordtime string, eventid string, url string, ip string ) STORED AS TEXTFILE”) # Convert RDDs of the lines DStream to DataFrame and run SQL query. This tool parses xml files automatically (independently of their structure), and explodes their arrays if needed, and inserts them in a new HiveQL table, to make this data accesible for data analysis. the table in the Hive metastore automatically inherits the schema, partitioning, and table properties of the existing data. This chapter describes how to drop a table in Hive. DataFrames can be constructed from a wide array of sources such as: structured data files, tables in Hive, external databases, or existing RDDs. # Creating an Pyspark dataframe from a hive table # Importing the train data, the test data and the scoring data data_train = sqlContext. If source is not specified, the default data source configured by spark. From Spark 2. A Datasource on top of Spark Datasource V1 APIs, that provides Spark support for Hive ACID transactions. Therefore, the Hive client library cannot create metastore tables even if you set datanucleus. In order to avoid hive bugs, we need to create an empty directory at “C:\tmp\hive“. Pyspark Joins by Example This entry was posted in Python Spark on January 27, 2018 by Will Summary: Pyspark DataFrames have a join method which takes three parameters: DataFrame on the right side of the join, Which fields are being joined on, and what type of join (inner, outer, left_outer, right_outer, leftsemi). This is the second way through which we can using the XML formatted file in Apache Spark. 06/12/2019; 6 minutes to read +2; In this article. sql(“DROP TABLE IF EXISTS csmessages_hive_table”) spark. Let's create table "reports" in the hive. REFRESH TABLE [db_name. With Spark, you can get started with big data processing, as it has built-in modules for streaming, SQL, machine learning and graph processing. Compressing Text Tables In Hive 01 June 2011 on hadoop, hive, ruby. Spark has API in Pyspark and Sparklyr, I choose Pyspark here, because Sparklyr API is very similar to Tidyverse. If you use pyspark it will excute spark executers on your laptop. The result is an enriched Hive table on HDFS which is filtered to only contain information that we care about. 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. html 2019-10-25 19:10:02 -0500. databricks:spark-csv_2. Next, create the MovieDetails table to query over. 6 and I aim to create external hive table like what I do in hive script. After checking the property in Ambari came to know there is spark warehouse directory where all the hive tables are created and it is not listed under hive databases. Data resides outside the Hive metastore. It provides high performance APIs for programming Apache Spark applications with C# and F#. Using HiveContext, you can create and find tables in the HiveMetaStore and write queries on it using HiveQL. Using PySpark allows us to perform preprocessing on Hadoop and take advantage of the parallel execution, along with the in-memory processing that Spark provides. There are a few ways to read data into Spark as a dataframe. from pyspark_llap. The save is method on DataFrame allows passing in a data source type. 5 (7,859 ratings) Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately. Simply put, an External Table is a table built directly on top of a folder within a data source. 2 When I execute the show tables; query I get the. but this did not help. format("orc"). That is the conversion of a local R data frame into a SparkDataFrame. I am using like in pySpark, which is always adding new data into table. In the older version of HDP i. Using partitions it’s easy to query a portion of data. First, create an SQL query inside a DB notebook and wait for the results. Specifying storage format for Hive tables. Import all tables in the MySQL retail_db to the hive database called retail_db. How to Save Spark DataFrame as Hive Table? Because of its in-memory computation, Spark is used to process the complex computation. Users who do not have an existing Hive deployment can still create a HiveContext. The command line client currently only supports an embedded server. Hive and Presto Clusters with Jupyter on AWS, Azure, and Oracle October 10, 2017 by Mikhail Stolpner and Qubole Updated January 15th, 2019 Jupyter™ Notebooks is one of the most popular IDE of choice among Python users. The second question I believe is regarding using environment variable like hive create table location. First, create an SQL query inside a DB notebook and wait for the results. If you do sqlCtx. Objective: Creating Hive tables is really an easy task. Thus, there is successful establishement of connection between Spark SQL and Hive. PySpark/Hive: how to CREATE TABLE with LazySimpleSerDe to convert boolean 't/'f'? I create a Hive DB and a temp Hive table and then SELECT * from it, like this:. Install Windows Server 2012R2 using Virtualbox VHD Upgrade MySQL 5. I hope you guys got an idea of what PySpark DataFrame is, why is it used in the industry and its features in this PySpark DataFrame tutorial. Sqoop command submitted by the end user is parsed by Sqoop and launches Hadoop Map only job to import or export data because Reduce phase is required only when aggregations are needed. This Jira has been LDAP enabled, if you are an ASF Committer, please use your LDAP Credentials to login. Or you can use the spark-sql client instead of hive. The following query is a simple example of selecting all columns from table_x and assigning the result to a spark data-frame. What are the Hive Partitions? Apache Hive organizes tables into partitions. To achieve the requirement, the following components are involved: Hive: Used to Store data; Spark 1. Therefore, the Hive client library cannot create metastore tables even if you set datanucleus. To do this, I first read in the partitioned avro file and get the schema of this file. table("default. Importing Data from Files into Hive Tables. Using HiveContext, you can create and find tables in the HiveMetaStore and write queries on it using HiveQL. Example Databases and Tables Example of animals table in zoo_a database. To correct this, we need to tell spark to use hive for metadata. Transfer parquet Hive table from one Hadoop cluster to another; Connect Excel to Cloudera Hive/Impala; Top Highest Interest US Savings Accounts; Top Posts & Pages. What if you would like to include this data in a Spark ML (machine. Apache Spark is a fast and general-purpose cluster computing system. In this blog post, we will see how to use Spark with Hive, particularly: - how to create and use Hive databases - how to create Hive tables - how to load data to Hive tables - how to insert data into Hive tables - how to read data from Hive tables - we will also see how to save dataframes to any Hadoop supported file system. init() import pyspark from pyspark. PySpark is the Python package that makes the magic happen. Users who do not have an existing Hive deployment can still create a HiveContext. Thus, there is successful establishement of connection between Spark SQL and Hive. A dataframe in Spark is similar to a SQL table, an R dataframe, or a pandas dataframe. In this case Hive is used as an ETL tool so to speak. Example Databases and Tables Example of animals table in zoo_a database. The first solution is to try to load the data and put the code into a try block, we try to read the first element from the RDD. When we create a table in Hive, it by default manages the data. It is conceptually equivalent to a table in a relational database or a data frame in R/Python, but with richer optimizations under the hood. Configuring the JDBC Interpreter for Apache Drill and Apache Hive. execute("show tables"). table2 on ' hive=HiveWarehouseSession. sql('CREATE DATABASE IF NOT EXISTS unit08lab1') hive. Once done with step 3. Sample_50pct_train"). Hive External Tables-We can also create an external table. On spark SQL , I am able to list all tables , but queries on hive bucketed tables are not returning records. You can vote up the examples you like or vote down the ones you don't like. A SparkSession can be used create DataFrame, register DataFrame as tables, execute SQL over tables, cache tables, and read parquet files. The setup We will use flume to fetch the tweets and enqueue them on kafka and flume to dequeue the data hence flume will act both as a kafka producer and consumer while kafka would be used as a channel to hold data. Sqoop Architecture Sqoop provides command line interface to the end users. The information that you provide in this clause enables the access driver to generate a Data Pump format file that contains the data and metadata from the Oracle database table. Install VSCode for PySpark/hive applications. # Drop the tables if it already exists # Create the tables to store your streams spark. How do I get pyspark to find my tables? spark. show(), it should show the correct schema. How to Save Spark DataFrame as Hive Table? Because of its in-memory computation, Spark is used to process the complex computation. Finally, we have populated the hive partitioned table with the data. Sample Data. , and default values for environment variables are. This chapter explains how to create a table and how to insert data into it. Read the data from the hive table. To create a Hive table using Spark SQL, we can use the following code:. but this did not help. But when you really want to create 1000 of tables in Hive based on the Source RDBMS tables and it's data types think about the Development Scripts Creation and Execution. Programming in Spark using PySpark. It tells Hive to refer to the data that is at an existing location outside the warehouse directory. Tables must be marked as transactional in order to support UPDATE and DELETE operations. build() 6) run following code in scala shell to view the hive table data: import com. 3 (327 ratings) Course Ratings are calculated from individual students' ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately. sql Run non-interactive script hive ‐f script. # Creating an Pyspark dataframe from a hive table # Importing the train data, the test data and the scoring data data_train = sqlContext. Apache Hive should be used for data warehousing requirements and when the programmers do not want to write complex mapreduce code. The command line client currently only supports an embedded server. 0) or createGlobalTempView on our spark Dataframe. 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. 1) create data frame for each of the hive table and replicate SQL and run on the Spark. If you are running as root or some other user that does not have HDFS privileges, you might not be able to create the corresponding directory in HDFS. A simple example demonstrating Spark SQL Hive integration. Treasure Data is a CDP that allows users to collect, store, and analyze their data on the cloud. Load the text file into Hive table. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution engine. Contribute to apache/spark development by creating an account on GitHub. Make sure the hive-site. 0, you can easily read data from Hive data warehouse and also write/append new data to Hive tables. 2 When I execute the show tables; query I get the. The result is that using Hive on HBase should be used conservatively. sql("SELECT * FROM my_db. Before we start with the SQL commands, it is good to know how HIVE stores the data. You'll learn to wrangle this data and build a whole machine learning pipeline to predict whether or not flights will be delayed. Hive comes with a command-line shell interface which can be used to create tables and execute queries. Previous Load Data Next USER DEFINED FUNCTIONS In this post we will discuss about how to implement spark sql in the pyspark. Compressing Text Tables In Hive 01 June 2011 on hadoop, hive, ruby. Also can help to access tables in the Hive MetaStore. Once done with step 3. Need help guys. -Databricks. PySpark Cheat Sheet: Spark in Python This PySpark cheat sheet with code samples covers the basics like initializing Spark in Python, loading data, sorting, and repartitioning. This is the git hub link to spark sql jupyter notebook There are two methods to create table from a dataframe. The samples included here use a clean installation of the Hortonworks Sandbox and query some of the sample tables included out of the box. You can also save this page to your account. Workshop Exercises This category is to create Exercises who are part of live training sessions. This chapter describes how to drop a table in Hive. Hive Buckets is nothing but another technique of decomposing data or decreasing the data into more manageable parts or equal parts. 3 (327 ratings) Course Ratings are calculated from individual students' ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately. Eg: query='create table result_table as select * from hive_db. Using HiveContext, you can create and find tables in the HiveMetaStore and write queries on it using HiveQL. You use the Hive Warehouse Connector API to access any managed Hive table from Spark. sql import SQLContext sc = pyspark. def registerFunction (self, name, f, returnType = StringType ()): """Registers a python function (including lambda function) as a UDF so it can be used in SQL statements. format("orc"). High compatibility In Apache Spark SQL, we can run unmodified Hive queries on existing warehouses. Once we have data of hive table in the Spark data frame, we can further transform it as per the business needs. Hive has this wonderful feature of partitioning — a way of dividing a table into related parts based on the values of certain columns. NET for Apache Spark v0. environ["JAVA_HOME"] = "C:\\PROGRA~1\\Java\\jdk1. Once the data is loaded, it can be analysed with SQL queries in Hive. OK, I Understand. Create a SparkSession with Hive supported. Import all tables in the MySQL retail_db to the hive database called retail_db. Hive metastore Parquet table conversion.