Work with Plaid Data in Apache Spark Using SQL

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Plaid JDBC Driver

Rapidly create and deploy powerful Java applications that integrate with Plaid account data including Assets, Investments, Liabilities, Transactions, and more!

Access and process Plaid Data in Apache Spark using the CData JDBC Driver.

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

The CData JDBC Driver offers unmatched performance for interacting with live Plaid data due to optimized data processing built into the driver. When you issue complex SQL queries to Plaid, the driver pushes supported SQL operations, like filters and aggregations, directly to Plaid 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 Plaid data using native data types.

Install the CData JDBC Driver for Plaid

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

Start a Spark Shell and Connect to Plaid Data

  1. Open a terminal and start the Spark shell with the CData JDBC Driver for Plaid JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for Plaid/lib/cdata.jdbc.plaid.jar
  2. With the shell running, you can connect to Plaid with a JDBC URL and use the SQL Context load() function to read a table.

    You can connect to Plaid using the embedded OAuth connectivity. When you connect, the Plaid OAuth endpoint opens in your browser. Log in and grant permissions to complete the OAuth process. See the OAuth section in the online Help documentation for more information on other OAuth authentication flows.

    Optionally set the Account Id property to return data related to a specific Account.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.plaid.jar

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

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

    scala> val plaid_df ="jdbc").option("url", "jdbc:plaid:AccountId=123456789;").option("dbtable","Transactions").option("driver","cdata.jdbc.plaid.PlaidDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the Plaid data as a temporary table:

    scala> plaid_df.registerTable("transactions")
  5. Perform custom SQL queries against the Data using commands like the one below:

    scala> plaid_df.sqlContext.sql("SELECT AccountId, Name FROM Transactions WHERE Name = Apple Store").collect.foreach(println)

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

Using the CData JDBC Driver for Plaid in Apache Spark, you are able to perform fast and complex analytics on Plaid data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 200+ CData JDBC Drivers and get started today.