PowerShell Scripting to Replicate BigQuery Data to MySQL

The CData Cmdlets for BigQuery offer live access to BigQuery data from within PowerShell. Using PowerShell scripts, you can easily automate regular tasks like data replication. This article will walk through using the CData Cmdlets for BigQuery and the CData Cmdlets for MySQL in PowerShell to replicate BigQuery data to a MySQL database.

After obtaining the needed connection properties, accessing BigQuery data in PowerShell and preparing for replication consists of four basic steps.

Google uses the OAuth authentication standard. To access Google APIs on behalf of individual users, you can use the embedded credentials or you can register your own OAuth app.

OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, you will need to register an application to obtain the OAuth JWT values.

In addition to the OAuth values, you will need to specify the DatasetId and ProjectId. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

Collecting BigQuery Data

1. Install the module:

   Install-Module GoogleBigQueryCmdlets

2. Connect to BigQuery:

   $googlebigquery = Connect-GoogleBigQuery -DataSetId $DataSetId -ProjectId $ProjectId

3. Retrieve the data from a specific resource:

   $data = Select-GoogleBigQuery -Connection $googlebigquery -Table "Orders"

   You can also use the Invoke-GoogleBigQuery cmdlet to execute pure SQL-92 statements:

   $data = Invoke-GoogleBigQuery -Connection $googlebigquery -Query 'SELECT * FROM Orders WHERE ShipCity = @ShipCity' -Params @{'@ShipCity'='New York'}

4. Save a list of the column names from the returned data.

   $columns = ($data | Get-Member -MemberType NoteProperty | Select-Object -Property Name).Name

Inserting BigQuery Data into the MySQL Database

With the data and column names collected, you are ready to replicate the data into a MySQL database.

1. Install the module:

   Install-Module MySQLCmdlets

2. Connect to MySQL, using the server address and port of the MySQL server, valid user credentials, and a specific database with the table in which the data will be replicated:

   $mysql = Connect-MySQL -User $User -Password $Password -Database $Database -Server $Server -Port $Port

3. Loop through the BigQuery data, store the values, and use the Add-MySQL cmdlet to insert the data into the MySQL database, one row at a time. In this example, the table will need to have the same name as the BigQuery resource (Orders) and to exist in the database.

   $data | % { $row = $_ $values = @() $columns | % { $col = $_ $values += $row.$($col) } Add-MySQL -Connection $mysql -Table "Orders" -Columns $columns -Values $values }

You have now replicated your BigQuery data to a MySQL database. This gives you freedom to work with BigQuery data in the same way that you work with other MySQL tables, whether that is performing analytics, building reports, or other business functions.

Notes

• Once you have connected to BigQuery and MySQL in PowerShell, you can pipe command results to perform the replication in a single line:

  Select-GoogleBigQuery -Connection $googlebigquery -Table "Orders" | % { $row = $_ $values = @() $columns | % { $col = $_ $values += $row.$($col) } Add-MySQL -Connection $mysql -Table "Orders" -Columns $columns -Values $values }

• If you wish to replicate the BigQuery data to another database using another PowerShell module, you will want to exclude the Columns, Connection, and Table columns from the data returned by the Select-GoogleBigQuery cmdlet since those columns are used to help pipe data from one CData cmdlet to another:

  $columns = ($data | Get-Member -MemberType NoteProperty | Select-Object -Property Name).Name | ? {$_ -NotIn @('Columns','Connection','Table')}