How to work with LINE Data in Apache Spark using SQL

Apache Spark is a fast and general engine for large-scale data processing. When paired with the CData JDBC Driver for LINE, Spark can work with live LINE data. This article describes how to connect to and query LINE data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live LINE data due to optimized data processing built into the driver. When you issue complex SQL queries to LINE, the driver pushes supported SQL operations, like filters and aggregations, directly to LINE and utilizes the embedded SQL engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can work with and analyze LINE data using native data types.

Install the CData JDBC Driver for LINE

Download the CData JDBC Driver for LINE installer, unzip the package, and run the JAR file to install the driver.

Start a Spark Shell and Connect to LINE Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for LINE JAR file as the jars parameter:

   
   $ spark-shell --jars /CData/CData JDBC Driver for LINE/lib/cdata.jdbc.api.jar
   

2. With the shell running, you can connect to LINE with a JDBC URL and use the SQL Context load() function to read a table.

   Start by setting the Profile connection property to the location of the LINE Profile on disk (e.g. C:\profiles\LINE.apip). Next, set the ProfileSettings connection property to the connection string for LINE (see below).

   LINE API Profile Settings

   The LINE Messaging API uses Channel Access Token authentication. To obtain a Channel Access Token:

   1. Log in to the LINE Developers Console at https://developers.line.biz
   2. Select your provider and open your Messaging API channel.
   3. Navigate to the Messaging API tab.
   4. Under Channel access token, click Issue to generate a long-lived token.
   5. Copy the generated token.

   After obtaining your Channel Access Token, set the following connection properties:

   • AuthScheme: Set this to APIKey.

   Set the following in the ProfileSettings connection property:

   • APIKey: Set this to your LINE Channel Access Token.

   Built-in Connection String Designer

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

   
   java -jar cdata.jdbc.api.jar
   

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

   

   Configure the connection to LINE, using the connection string generated above.

   
   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\LINE.apip;ProfileSettings='APIKey=your_channel_access_token;';AuthScheme=APIKey;").option("dbtable","ReplyMessageDelivery").option("driver","cdata.jdbc.api.APIDriver").load()
   

3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the LINE data as a temporary table:

   scala> api_df.registerTable("replymessagedelivery")

5. Perform custom SQL queries against the Data using commands like the one below:

   scala> api_df.sqlContext.sql("SELECT DeliveryDate, DeliveredCount FROM ReplyMessageDelivery WHERE DeliveryDate = 20240115").collect.foreach(println)

   You will see the results displayed in the console, similar to the following:

   

Using the CData JDBC Driver for LINE in Apache Spark, you are able to perform fast and complex analytics on LINE data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the hundreds of CData JDBC Drivers and get started today.