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Load Elasticsearch Data to a Database Using Embulk


Use CData JDBC drivers with the open source ETL/ELT tool Embulk to load Elasticsearch data to a database.

Embulk is an open source bulk data loader. When paired with the CData JDBC Driver for Elasticsearch, Embulk easily loads data from Elasticsearch to any supported destination. In this article, we explain how to use the CData JDBC Driver for Elasticsearch in Embulk to load Elasticsearch data to a MySQL dtabase.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Elasticsearch data. When you issue complex SQL queries to Elasticsearch, the driver pushes supported SQL operations, like filters and aggregations, directly to Elasticsearch and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Configure a JDBC Connection to Elasticsearch Data

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 Elasticsearch\lib).

Embulk supports JDBC connectivity, so you can easily connect to Elasticsearch and execute SQL queries. Before creating a bulk load job, create a JDBC URL for authenticating with Elasticsearch.

Set the Server and Port connection properties to connect. To authenticate, set the User and Password properties, PKI (public key infrastructure) properties, or both. To use PKI, set the SSLClientCert, SSLClientCertType, SSLClientCertSubject, and SSLClientCertPassword properties.

The data provider uses X-Pack Security for TLS/SSL and authentication. To connect over TLS/SSL, prefix the Server value with 'https://'. Note: TLS/SSL and client authentication must be enabled on X-Pack to use PKI.

Once the data provider is connected, X-Pack will then perform user authentication and grant role permissions based on the realms you have configured.

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Elasticsearch JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

java -jar cdata.jdbc.elasticsearch.jar

Fill in the connection properties and copy the connection string to the clipboard.

Below is a typical JDBC connection string for Elasticsearch:

jdbc:elasticsearch:Server=127.0.0.1;Port=9200;User=admin;Password=123456;

Load Elasticsearch Data in Embulk

After installing the CData JDBC Driver and creating a JDBC connection string, install the required Embulk plugins.

Install Embulk Input & Output Plugins

  1. Install the JDBC Input Plugin in Embulk.
    https://github.com/embulk/embulk-input-jdbc/tree/master/embulk-input-jdbc
    2. embulk gem install embulk-input-jdbc
  2. In this article, we use MySQL as the destination database. You can also choose SQL Server, PostgreSQL, or Google BigQuery as the destination using the output Plugins.
    https://github.com/embulk/embulk-output-jdbc/tree/master/embulk-output-mysql embulk gem install embulk-output-mysql

With the input and output plugins installed, we are ready to load Elasticsearch data into MySQL using Embulk.

Create a Job to Load Elasticsearch Data

Start by creating a config file in Embulk, using a name like elasticsearch-mysql.yml.

  1. For the input plugin options, use the CData JDBC Driver for Elasticsearch, including the path to the driver JAR file, the driver class (e.g. cdata.jdbc.elasticsearch.ElasticsearchDriver), and the JDBC URL from above
  2. For the output plugin options, use the values and credentials for the MySQL database

Sample Config File (elasticsearch-mysql.yml)

in: type: jdbc driver_path: C:\Program Files\CData[product_name] 20xx\lib\cdata.jdbc.elasticsearch.jar driver_class: cdata.jdbc.elasticsearch.ElasticsearchDriver url: jdbc:elasticsearch:Server=127.0.0.1;Port=9200;User=admin;Password=123456; table: "Orders" out: type: mysql host: localhost database: DatabaseName user: UserId password: UserPassword table: "Orders" mode: insert

After creating the file, run the Embulk job.

embulk run elasticsearch-mysql.yml

After running the the Embulk job, find the Salesforce data in the MySQL table.

Load Filtered Elasticsearch Data

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.elasticsearch.jar driver_class: cdata.jdbc.elasticsearch.ElasticsearchDriver url: jdbc:elasticsearch:Server=127.0.0.1;Port=9200;User=admin;Password=123456; query: "SELECT OrderName, Freight FROM Orders WHERE [RecordId] = 1" out: type: mysql host: localhost database: DatabaseName user: UserId password: UserPassword table: "Orders" mode: insert

More Information & Free Trial

By using CData JDBC Driver for Elasticsearch as a connector, Embulk can integrate Elasticsearch 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.