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Embulk is an open source bulk data loader. When paired with the CData JDBC Driver for Apache Hive, Embulk easily loads data from Hive to any supported destination. In this article, we explain how to use the CData JDBC Driver for Apache Hive in Embulk to load Hive data to a MySQL dtabase.
With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Hive data. When you issue complex SQL queries to Hive, the driver pushes supported SQL operations, like filters and aggregations, directly to Hive and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Before creating a bulk load job in Embulk, note the installation location for the JAR file for the JDBC Driver (typically C:\Program Files\CData\CData JDBC Driver for Apache Hive\lib).
Embulk supports JDBC connectivity, so you can easily connect to Hive and execute SQL queries. Before creating a bulk load job, create a JDBC URL for authenticating with Hive.
Set the Server, Port, TransportMode, and AuthScheme connection properties to connect to Hive.For assistance in constructing the JDBC URL, use the connection string designer built into the Hive JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.apachehive.jar
Fill in the connection properties and copy the connection string to the clipboard.
👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)Below is a typical JDBC connection string for Hive:
jdbc:apachehive:Server=127.0.0.1;Port=10000;TransportMode=BINARY;
After installing the CData JDBC Driver and creating a JDBC connection string, install the required Embulk plugins.
embulk gem install embulk-input-jdbc
embulk gem install embulk-output-mysql
With the input and output plugins installed, we are ready to load Hive data into MySQL using Embulk.
Start by creating a config file in Embulk, using a name like apachehive-mysql.yml.
in: type: jdbc driver_path: C:\Program Files\CData[product_name] 20xx\lib\cdata.jdbc.apachehive.jar driver_class: cdata.jdbc.apachehive.ApacheHiveDriver url: jdbc:apachehive:Server=127.0.0.1;Port=10000;TransportMode=BINARY; table: "Customers" out: type: mysql host: localhost database: DatabaseName user: UserId password: UserPassword table: "Customers" mode: insert
After creating the file, run the Embulk job.
embulk run apachehive-mysql.yml
After running the the Embulk job, find the Salesforce data in the MySQL table.
In addition to loading data directly from a table, you can use a custom SQL query to have more granular control of the data loaded. You can also perform increment loads by setting a last updated column in a SQL WHERE clause in the query field.
in: type: jdbc driver_path: C:\Program Files\CData[product_name] 20xx\lib\cdata.jdbc.apachehive.jar driver_class: cdata.jdbc.apachehive.ApacheHiveDriver url: jdbc:apachehive:Server=127.0.0.1;Port=10000;TransportMode=BINARY; query: "SELECT City, CompanyName FROM Customers WHERE [RecordId] = 1" out: type: mysql host: localhost database: DatabaseName user: UserId password: UserPassword table: "Customers" mode: insert
By using CData JDBC Driver for Apache Hive as a connector, Embulk can integrate Hive data into your data load jobs. And with drivers for more than 200+ other enterprise sources, you can integrate any enterprise SaaS, big data, or NoSQL source as well. Download a 30-day free trial and get started today.
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