Work with Paylocity Data in Apache Spark Using SQL

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Paylocity JDBC Driver

Rapidly create and deploy powerful Java applications that integrate with Paylocity.



Access and process Paylocity 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 Paylocity, Spark can work with live Paylocity data. This article describes how to connect to and query Paylocity data from a Spark shell.

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

Install the CData JDBC Driver for Paylocity

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

Start a Spark Shell and Connect to Paylocity Data

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

    Set the following to establish a connection to Paylocity:

    • RSAPublicKey: Set this to the RSA Key associated with your Paylocity, if the RSA Encryption is enabled in the Paylocity account.

      This property is required for executing Insert and Update statements, and it is not required if the feature is disabled.

    • UseSandbox: Set to true if you are using sandbox account.
    • CustomFieldsCategory: Set this to the Customfields category. This is required when IncludeCustomFields is set to true. The default value for this property is PayrollAndHR.
    • Key: The AES symmetric key(base 64 encoded) encrypted with the Paylocity Public Key. It is the key used to encrypt the content.

      Paylocity will decrypt the AES key using RSA decryption.
      It is an optional property if the IV value not provided, The driver will generate a key internally.

    • IV: The AES IV (base 64 encoded) used when encrypting the content. It is an optional property if the Key value not provided, The driver will generate an IV internally.

    Connect Using OAuth Authentication

    You must use OAuth to authenticate with Paylocity. OAuth requires the authenticating user to interact with Paylocity using the browser. For more information, refer to the OAuth section in the Help documentation.

    The Pay Entry API

    The Pay Entry API is completely separate from the rest of the Paylocity API. It uses a separate Client ID and Secret, and must be explicitly requested from Paylocity for access to be granted for an account. The Pay Entry API allows you to automatically submit payroll information for individual employees, and little else. Due to the extremely limited nature of what is offered by the Pay Entry API, we have elected not to give it a separate schema, but it may be enabled via the UsePayEntryAPI connection property.

    Please be aware that when setting UsePayEntryAPI to true, you may only use the CreatePayEntryImportBatch & MergePayEntryImportBatchgtable stored procedures, the InputTimeEntry table, and the OAuth stored procedures. Attempts to use other features of the product will result in an error. You must also store your OAuthAccessToken separately, which often means setting a different OAuthSettingsLocation when using this connection property.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.paylocity.jar

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

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

    scala> val paylocity_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:paylocity:OAuthClientID=YourClientId;OAuthClientSecret=YourClientSecret;RSAPublicKey=YourRSAPubKey;Key=YourKey;IV=YourIV;").option("dbtable","Employee").option("driver","cdata.jdbc.paylocity.PaylocityDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the Paylocity data as a temporary table:

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

    scala> paylocity_df.sqlContext.sql("SELECT FirstName, LastName FROM Employee WHERE EmployeeId = 1234").collect.foreach(println)

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

Using the CData JDBC Driver for Paylocity in Apache Spark, you are able to perform fast and complex analytics on Paylocity 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.