Apache Spark Connector for PowerShell

Prerequisites

Before we begin, make sure you meet the following prerequisite: Java Runtime Environment (JRE) or Java Development Kit (JDK) must be installed on your system.

• Minimum required version: Java 8
  • Amazon Corretto 8
  • Oracle JRE 8
• Recommended Java version: Java 21
  • Amazon Corretto 21
  • Oracle JRE 21

If your JDBC Driver targets a different Java version (e.g., 11 / 17 / 21), install the corresponding or newer Java version.

Download Apache Spark JDBC driver

To connect to Apache Spark in , you will have to download JDBC driver for it, which we will use in later steps. Let's perform these little steps right away:

1. Visit MVN Repository.
2. Download the JDBC driver, and save it locally, e.g. to D:\Drivers\JDBC\hive-jdbc-standalone.jar.
3. Make sure to download the standalone version of the Apache Hive JDBC driver to avoid Java library dependency errors, e.g., hive-jdbc-4.0.1-standalone.jar (commonly used driver to connect to Spark).
4. Done! That was easy, wasn't it? Let's proceed to the next step.

Create ODBC Data Source (DSN) based on ZappySys JDBC Bridge Driver

Step-by-step instructions

To get data from Apache Spark using PowerShell we first need to create a DSN (Data Source) which will access data from Apache Spark. We will later be able to read data using PowerShell. Perform these steps:

1. Download and install ODBC PowerPack.

2. Open ODBC Data Sources (x64):

   

3. Create a User data source (User DSN) based on ZappySys JDBC Bridge Driver:

   ZappySys JDBC Bridge Driver

   
   • Create and use User DSN if the client application is run under a User Account. This is an ideal option in design-time, when developing a solution, e.g. in Visual Studio 2019. Use it for both type of applications - 64-bit and 32-bit.
   • Create and use System DSN if the client application is launched under a System Account, e.g. as a Windows Service. Usually, this is an ideal option to use in a production environment. Use ODBC Data Source Administrator (32-bit), instead of 64-bit version, if Windows Service is a 32-bit application.

4. Now, we need to configure the JDBC connection in the new ODBC data source. Simply enter the Connection string, credentials, configure other settings, and then click Test Connection button to test the connection:

   ApacheSparkDSN

   jdbc:hive2://spark-thrift-server-host:10000

   D:\Drivers\JDBC\hive-jdbc-standalone.jar

   []

   

   Use these values when setting parameters:

   • Connection string: jdbc:hive2://spark-thrift-server-host:10000
   • JDBC driver file(s): D:\Drivers\JDBC\hive-jdbc-standalone.jar
   • Connection parameters: []

5. You should see a message saying that connection test is successful:

   

   Otherwise, if you are getting an error, check out our Community for troubleshooting tips.

6. We are at the point where we can preview a SQL query. For more SQL query examples visit JDBC Bridge documentation:

   ApacheSparkDSN

   -- Basic SELECT with a WHERE clause
   SELECT
       id,
       name,
       salary
   FROM employees
   WHERE department = 'Sales';

   

   -- Basic SELECT with a WHERE clause
   SELECT
       id,
       name,
       salary
   FROM employees
   WHERE department = 'Sales';

   You can also click on the <Select Table> dropdown and select a table from the list.

   The ZappySys JDBC Bridge Driver acts as a transparent intermediary, passing SQL queries directly to the JDBC driver, which then handles the query execution. This means the Bridge Driver simply relays the SQL query without altering it.

   Some JDBC drivers don't support INSERT/UPDATE/DELETE statements, so you may get an error saying "action is not supported" or a similar one. Please, be aware, this is not the limitation of ZappySys JDBC Bridge Driver, but is a limitation of the specific JDBC driver you are using.

7. Click OK to finish creating the data source.

Video Tutorial

Read Apache Spark data in PowerShell

Sometimes, you need to quickly access and work with your Apache Spark data in PowerShell. Whether you need a quick data overview or the complete dataset, this article will guide you through the process. Here are some common scenarios:

• Quickly peek at Apache Spark data
• Monitor data constantly in your console

• Export data to a CSV file so that it can be sliced and diced in Excel
• Export data to a JSON file so that it can ingested by other processes
• Export data to an HTML file for user-friendly view and easy sharing
• Create a schedule to make it an automatic process

• Store data internally for analysis or for further ETL processes
• Create a schedule to make it an automatic process

• Integrate data with other systems via external APIs

In this article, we will delve deeper into how to quickly view the data in PowerShell terminal and how to save it to a file. But let's stop talking and get started!

Reading individual fields

1. Open your favorite PowerShell IDE (we are using Visual Studio Code).

2. Use this code snippet to read the data using ApacheSparkDSN data source:

   "DSN=ApacheSparkDSN"

   

   For your convenience, here is the whole PowerShell script:

   # Configure connection string and query
   $connectionString = "DSN=ApacheSparkDSN"
   $query = "SELECT * FROM Customers"
   
   # Instantiate OdbcDataAdapter and DataTable
   $adapter = New-Object System.Data.Odbc.OdbcDataAdapter($query, $connectionString)
   $table = New-Object System.Data.DataTable
   
   # Fill the table with data
   $adapter.Fill($table)
   
   # Since we know we will be reading just 4 columns, let's define format for those 4 columns, each separated by a tab
   $format = "{0}`t{1}`t{2}`t{3}"
   
   # Display data in the console
   foreach ($row in $table.Rows)
   {
       # Construct line based on the format and individual Apache Spark fields
       $line = $format -f ($row["CustomerId"], $row["CompanyName"], $row["Country"], $row["Phone"])
       Write-Host $line
   }
   

   Access specific Apache Spark table field using this code snippet:

   $field = $row["ColumnName"]

   You will find more info on how to manipulate DataTable.Rows property in Microsoft .NET reference.
   For demonstration purposes we are using sample tables which may not be available in Apache Spark.

3. To read values in a console, save the script to a file and then execute this command inside PowerShell terminal:

   
   You can also use even a simpler command inside the terminal, e.g.:

   . 'C:\Users\john\Documents\dsn.ps1'

Retrieving all fields

However, there might be case, when you want to retrieve all columns of a query. Here is how you do it:

"DSN=ApacheSparkDSN"

Again, for your convenience, here is the whole PowerShell script:

# Configure connection string and query
$connectionString = "DSN=ApacheSparkDSN"
$query = "SELECT CustomerId, CompanyName, Country, Phone FROM Customers"

# Instantiate OdbcDataAdapter and DataTable
$adapter = New-Object System.Data.Odbc.OdbcDataAdapter($query, $connectionString)
$table = New-Object System.Data.DataTable

# Fill the table with data
$adapter.Fill($table)

# Display data in the console
foreach ($row in $table.Rows) {
    $line = ""
    foreach ($column in $table.Columns) {
        $value = $row[$column.ColumnName]

        # Let's handle NULL values
        if ($value -is [DBNull])
        {
            $value = "(NULL)"
        }
        $line += $value + "`t"
    }
    Write-Host $line
}

SELECT * FROM Customers LIMIT 10

Using a full ODBC connection string

In the previous steps we used a very short format of ODBC connection string - a DSN. Yet sometimes you don't want a dependency on an ODBC data source (and an extra step). In those times, you can define a full connection string and skip creating an ODBC data source entirely. Let's see below how to accomplish that in the below steps:

1. Open ODBC data source configuration and click Copy settings:
   

   ZappySys JDBC Bridge Driver - Configuration [Version: 2.0.1.10418]

   ZappySys JDBC Bridge Driver - Apache Spark

   Apache Spark Connector lets you connect to Apache Spark, a unified engine for large-scale data analytics.

   ApacheSparkDSN

   
2. The window opens, telling us the connection string was successfully copied to the clipboard:
3. Then just paste the connection string into your script:
4. You are good to go! The script will execute the same way as using a DSN.

Limitations of using a full connection string

Despite using a full ODBC connection string may be very convenient it comes with a limitation: it's length is limited to 1024 symbols (or sometimes more). It usually happens when API provider generates a very long Refresh Token when OAuth is at play. If you are using such a long ODBC connection string, you may get this error:

"Connection string exceeds maximum allowed length of 1024"

But there is a solution to this by storing the full connection string in a file. Follow the steps below to achieve this:

1. Open your ODBC data source.
2. Click Copy settings button to copy a full connection string (see the previous section on how to accomplish that).
3. Then create a new file, let's say, in C:\temp\odbc-connection-string.txt.
4. Continue by pasting the copied connection string into a newly created file and save it.
5. Finally, the last step! Just construct a shorter ODBC connection string using this format:

   DRIVER={ZappySys JDBC Bridge Driver};SettingsFile=C:\temp\odbc-connection-string.txt

6. Our troubles are over! Now you should be able to use this connection string in PowerShell with no problems.

Write Apache Spark data to a file in PowerShell

Save data to a CSV file

Export data to a CSV file so that it can be sliced and diced in Excel:

# Configure connection string and query
$connectionString = "DSN=ApacheSparkDSN"
$query = "SELECT * FROM Customers"

# Instantiate OdbcDataAdapter and DataTable
$adapter = New-Object System.Data.Odbc.OdbcDataAdapter($query, $connectionString)
$table = New-Object System.Data.DataTable

# Fill the table with data
$adapter.Fill($table)

# Export table data to a file
$table | ConvertTo-Csv -NoTypeInformation -Delimiter "`t" | Out-File "C:\Users\john\saved-data.csv" -Force

Save data to a JSON file

Export data to a JSON file so that it can ingested by other processes (use the above script, but change this part):

# Export table data to a file
$table | ConvertTo-Json | Out-File "C:\Users\john\saved-data.json" -Force

Save data to an HTML file

Export data to an HTML file for user-friendly view and easy sharing (use the above script, but change this part):

# Export table data to a file
$table | ConvertTo-Html | Out-File "C:\Users\john\saved-data.html" -Force

Centralized data access via Data Gateway

In some situations, you may need to provide Apache Spark data access to multiple users or services. Configuring the data source on a Data Gateway creates a single, centralized connection point for this purpose.

This configuration provides two primary advantages:

• Centralized data access
  The data source is configured once on the gateway, eliminating the need to set it up individually on each user's machine or application. This significantly simplifies the management process.
• Centralized access control
  Since all connections route through the gateway, access can be governed or revoked from a single location for all users.

If you need any of these requirements, you will have to create a data source in Data Gateway to connect to Apache Spark, and to create an ODBC data source to connect to Data Gateway in PowerShell.

Let's not wait and get going!

Creating Apache Spark data source in Gateway

In this section we will create a data source for Apache Spark in Data Gateway. Let's follow these steps to accomplish that:

1. Search for gateway in Windows Start Menu and open ZappySys Data Gateway Configuration:

   

2. Go to Users tab and follow these steps to add a Data Gateway user:

   • Click Add button
   • In Login field enter username, e.g., john
   • Then enter a Password
   • Check Is Administrator checkbox
   • Click OK to save
   

3. Now we are ready to add a data source:

   • Click Add button
   • Give Datasource a name (have it handy for later)
   • Then select Native - ZappySys JDBC Bridge Driver
   • Finally, click OK
   ApacheSparkDSN

   ZappySys JDBC Bridge Driver

   

4. When the ZappySys JDBC Bridge Driver configuration window opens, configure the Data Source the same way you configured it in ODBC Data Sources (64-bit), in the beginning of this article.

5. Very important step. Now, after creating or modifying the data source make sure you:

   • Click the Save button to persist your changes.
   • Hit Yes, once asked if you want to restart the Data Gateway service.

   This will ensure all changes are properly applied:

   
   Skipping this step may result in the new settings not taking effect and, therefore you will not be able to connect to the data source.

Creating ODBC data source for Data Gateway

In this part we will create ODBC data source to connect to Data Gateway from PowerShell. To achieve that, let's perform these steps:

1. Open ODBC Data Sources (x64):

   

2. Create a User data source (User DSN) based on ODBC Driver 17 for SQL Server:

   ODBC Driver 17 for SQL Server

   
   If you don't see ODBC Driver 17 for SQL Server driver in the list, choose a similar version driver.

3. Then set a Name of the data source (e.g. Gateway) and the address of the Data Gateway:

   GatewayDSN

   localhost,5000

   
   Make sure you separate the hostname and port with a comma, e.g. localhost,5000.

4. Proceed with authentication part:

   • Select SQL Server authentication
   • In Login ID field enter the user name you used in Data Gateway, e.g., john
   • Set Password to the one you configured in Data Gateway
   

5. Then set the default database property to ApacheSparkDSN (the one we used in Data Gateway):

   ApacheSparkDSN

   

6. Continue by checking Trust server certificate option:

   

7. Once you do that, test the connection:

   

8. If connection is successful, everything is good:

   

9. Done!

We are ready to move to the final step. Let's do it!

Accessing data in PowerShell via Data Gateway

Finally, we are ready to read data from Apache Spark in PowerShell via Data Gateway. Follow these final steps:

1. Go back to PowerShell.

2. Use this code snippet to read the data using GatewayDSN data source:

   "DSN=GatewayDSN"

   

   For your convenience, here is the whole PowerShell script:

   # Configure connection string and query
   $connectionString = "DSN=GatewayDSN"
   $query = "SELECT * FROM Customers"
   
   # Instantiate OdbcDataAdapter and DataTable
   $adapter = New-Object System.Data.Odbc.OdbcDataAdapter($query, $connectionString)
   $table = New-Object System.Data.DataTable
   
   # Fill the table with data
   $adapter.Fill($table)
   
   # Since we know we will be reading just 4 columns, let's define format for those 4 columns, each separated by a tab
   $format = "{0}`t{1}`t{2}`t{3}"
   
   # Display data in the console
   foreach ($row in $table.Rows)
   {
       # Construct line based on the format and individual Apache Spark fields
       $line = $format -f ($row["CustomerId"], $row["CompanyName"], $row["Country"], $row["Phone"])
       Write-Host $line
   }
   

   Access specific Apache Spark table field using this code snippet:

   $field = $row["ColumnName"]

   You will find more info on how to manipulate DataTable.Rows property in Microsoft .NET reference.
   For demonstration purposes we are using sample tables which may not be available in Apache Spark.

3. Read the data the same way we discussed at the beginning of this article.

4. That's it!

Now you can connect to Apache Spark data in PowerShell via the Data Gateway.

Troubleshooters & resources (JDBC Bridge Driver)

Below are some useful community articles to help you troubleshoot and configure the ZappySys JDBC Bridge Driver:

• How to combine multiple JAR files
  Learn how to merge multiple .jar dependencies when your JDBC driver requires more than one file.
• How to fix JBR error: “Data lake is not available / Unable to verify trust for server certificate chain”
  Resolve SSL or certificate validation issues encountered during JDBC connections.
• System Exception: “Java is not installed or not accessible”
  Fix Java path or environment issues that prevent the JDBC Bridge from launching Java.
• JDBC Bridge Driver disconnect from Java host error
  Troubleshoot unexpected disconnection problems between SSIS and the Java process.
• Error: Could not open jvm.cfg while using JDBC Bridge Driver
  Resolve JVM configuration path errors during driver initialization.
• How to enable JDBC Bridge Driver logging
  Enable detailed driver logging for better visibility during troubleshooting.
• How to pass JDBC connection parameters (not by URL)
  Learn how to specify connection properties programmatically instead of embedding them in the JDBC URL.
• How to fix JDBC Bridge error: “No connection could be made because the target machine actively refused it”
  Troubleshoot firewall or local port binding issues preventing communication with the Java host.
• How to use JDBC Bridge options (System Property for Java command line, e.g., classpath, proxy)
  Configure custom Java options like classpath and proxy using JDBC Bridge system properties.

Conclusion

In this article we showed you how to connect to Apache Spark in PowerShell and integrate data without any coding, saving you time and effort. It's worth noting that ZappySys JDBC Bridge Driver allows you to connect not only to Apache Spark, but to any Java application that supports JDBC (just use a different JDBC driver and configure it appropriately).

We encourage you to download Apache Spark Connector for PowerShell and see how easy it is to use it for yourself or your team.

If you have any questions, feel free to contact ZappySys support team. You can also open a live chat immediately by clicking on the chat icon below.

Download Apache Spark Connector for PowerShell Documentation

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