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Connect to Azure Data Lake Storage Data in Google Apps Script



Use CData Connect Cloud to access Azure Data Lake Storage data in Google Apps Script.

Google Apps Script empowers users to build custom functionality within their Google documents, including Google Sheets and Google Docs. Apps Script natively supports SQL Server connectivity via JDBC, providing a powerful extensibility tool for connecting Google cloud applications to external data. Paired with the SQL connectivity offered by CData Connect Cloud, users can easily access live Azure Data Lake Storage data directly from within their Google documents.

This article shows how to connect to Azure Data Lake Storage in Connect Cloud and provides sample scripting for processing Azure Data Lake Storage data in a Google Spreadsheet.

Configure Azure Data Lake Storage Connectivity for Google Apps Scripts

Connectivity to Azure Data Lake Storage from Google Apps Scripts is made possible through CData Connect Cloud. To work with Azure Data Lake Storage data from Google Apps Scripts, we start by creating and configuring a Azure Data Lake Storage connection.

CData Connect Cloud uses a straightforward, point-and-click interface to connect to data sources.

  1. Log into Connect Cloud, click Connections and click Add Connection
  2. Select "Azure Data Lake Storage" from the Add Connection panel
  3. Enter the necessary authentication properties to connect to Azure Data Lake Storage.

    Authenticating to a Gen 1 DataLakeStore Account

    Gen 1 uses OAuth 2.0 in Azure AD for authentication.

    For this, an Active Directory web application is required. You can create one as follows:

    1. Sign in to your Azure Account through the .
    2. Select "Azure Active Directory".
    3. Select "App registrations".
    4. Select "New application registration".
    5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
    6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
    7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

    To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

    • Schema: Set this to ADLSGen1.
    • Account: Set this to the name of the account.
    • OAuthClientId: Set this to the application Id of the app you created.
    • OAuthClientSecret: Set this to the key generated for the app you created.
    • TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
    • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

    Authenticating to a Gen 2 DataLakeStore Account

    To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

    • Schema: Set this to ADLSGen2.
    • Account: Set this to the name of the account.
    • FileSystem: Set this to the file system which will be used for this account.
    • AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
    • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
  4. Click Create & Test
  5. Navigate to the Permissions tab in the Add Azure Data Lake Storage Connection page and update the User-based permissions.

Add a Personal Access Token

If you are connecting from a service, application, platform, or framework that does not support OAuth authentication, you can create a Personal Access Token (PAT) to use for authentication. Best practices would dictate that you create a separate PAT for each service, to maintain granularity of access.

  1. Click on your username at the top right of the Connect Cloud app and click User Profile.
  2. On the User Profile page, scroll down to the Personal Access Tokens section and click Create PAT.
  3. Give your PAT a name and click Create.
  4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured, you are ready to connect to Azure Data Lake Storage data from Google Apps Script.

Connect to Azure Data Lake Storage Data from Apps Script

At this point, you should have configured a connection Azure Data Lake Storage in Connect Cloud. All that is left new is to use Google Apps Script to access Connect Cloud and work with your Azure Data Lake Storage data in Google Sheets.

In this section, you will create a script (with a menu option to call the script) to populate a spreadsheet with Azure Data Lake Storage data. We have created a sample script and explained the different parts. You can view the raw script at the and of the article.

1. Create an Empty Script

To create a script for your Google Sheet, click Tools Script editor from the Google Sheets menu:

Open script editor

2. Declare Class Variables

Create a handful of class variables to be available for any functions created in the script.

//replace the variables in this block with real values as needed
var address = 'tds.cdata.com:14333';
var user = 'CONNECT_USER'; // user@mydomain.com
var userPwd = 'CONNECT_USER_PAT';
var db = 'ADLS1';

var dbUrl = 'jdbc:sqlserver://' + address + ';databaseName=' + db;

3. Add a Menu Option

This function adds a menu option to your Google Sheet, allowing you to use the UI to call your function.

function onOpen() {
  var spreadsheet = SpreadsheetApp.getActive();
  var menuItems = [
    {name: 'Write data to a sheet', functionName: 'connectToADLSData'}
  ];
  spreadsheet.addMenu('Azure Data Lake Storage Data', menuItems);
} 
The newly added Menu option.

4. Write a Helper Function

This function is used to find the first empty row in a spreadsheet.

/*
 * Finds the first empty row in a spreadsheet by scanning an array of columns
 * @return The row number of the first empty row.
 */
function getFirstEmptyRowByColumnArray(spreadSheet, column) {
  var column = spreadSheet.getRange(column + ":" + column);
  var values = column.getValues(); // get all data in one call
  var ct = 0;
  while ( values[ct] && values[ct][0] != "" ) {
    ct++;
  }
  return (ct+1);
}

5. Write a Function to Write Azure Data Lake Storage Data to a Spreadsheet

The function below writes the Azure Data Lake Storage data, using the Google Apps Script JDBC functionality to connect to Connect Cloud, SELECT data, and populate a spreadsheet. When the script is run, two input boxes will appear:

The first one asks the user to input the name of a sheet to hold the data (if the spreadsheet does not exist, the function creates it).

Input box for sheet selection.

The second asks the user to input the name of a Azure Data Lake Storage table to read. If an invalid table is chosen, an error message appears and the function is exited.

Input box for table selection.

Note, while the function is designed for use as a menu option, you can extend it for use as a spreadsheet formula.

/*
 * Reads data from a specified Azure Data Lake Storage 'table' and writes it to the specified sheet.
 *    (If the specified sheet does not exist, it is created.)
 */
function connectToADLSData() {
  var thisWorkbook = SpreadsheetApp.getActive();

  //select a sheet and create it if it does not exist
  var selectedSheet = Browser.inputBox('Which sheet would you like the data to post to?',Browser.Buttons.OK_CANCEL);
  if (selectedSheet == 'cancel')
    return;

  if (thisWorkbook.getSheetByName(selectedSheet) == null)
    thisWorkbook.insertSheet(selectedSheet);
  var resultSheet = thisWorkbook.getSheetByName(selectedSheet);
  var rowNum = 2;

  //select a Azure Data Lake Storage 'table'
  var table = Browser.inputBox('Which table would you like to pull data from?',Browser.Buttons.OK_CANCEL);
  if (table == 'cancel')
    return;

  var name = Jdbc.getConnection(dbUrl, {
    user: user, 
    password: userPwd
	}	
  );

  //confirm that var table is a valid table/view
  var dbMetaData = name.getMetaData();
  var tableSet = dbMetaData.getTables(null, null, table, null);
  var validTable = false;
  while (tableSet.next()) {
    var tempTable = tableSet.getString(3);
    if (table.toUpperCase() == tempTable.toUpperCase()){
      table = tempTable;
      validTable = true;
      break;
    }
  } 
  tableSet.close();
  if (!validTable) {
    Browser.msgBox("Invalid table name: " + table, Browser.Buttons.OK);
    return;
  }

  var stmt = name.createStatement();

  var results = stmt.executeQuery('SELECT * FROM ' + table);
  var rsmd = results.getMetaData();
  var numCols = rsmd.getColumnCount();

  //if the sheet is empty, populate the first row with the headers
  var firstEmptyRow = getFirstEmptyRowByColumnArray(resultSheet, "A");
  if (firstEmptyRow == 1) {
    //collect column names
    var headers = new Array(new Array(numCols));
    for (var col = 0; col < numCols; col++){
      headers[0][col] = rsmd.getColumnName(col+1);
    }
    resultSheet.getRange(1, 1, headers.length, headers[0].length).setValues(headers);
  } else {
    rowNum = firstEmptyRow;
  }

  //write rows of Azure Data Lake Storage data to the sheet
  var values = new Array(new Array(numCols));
  while (results.next()) {
    for (var col = 0; col < numCols; col++) {
      values[0][col] = results.getString(col + 1);
    }
    resultSheet.getRange(rowNum, 1, 1, numCols).setValues(values);
    rowNum++;
  }

  results.close();
  stmt.close();
}
  

When the function is completed, you have a spreadsheet populated with your Azure Data Lake Storage data, and you can now leverage all of the calculating, graphing, and charting functionality of Google Sheets anywhere you have access to the Internet.


Complete Google Apps Script

//replace the variables in this block with real values as needed
var address = 'tds.cdata.com:14333';
var user = 'CONNECT_USER'; // user@mydomain.com
var userPwd = 'CONNECT_USER_PAT';
var db = 'ADLS1';

var dbUrl = 'jdbc:sqlserver://' + address + ';databaseName=' + db;

function onOpen() {
  var spreadsheet = SpreadsheetApp.getActive();
  var menuItems = [
    {name: 'Write table data to a sheet', functionName: 'connectToADLSData'}
  ];
  spreadsheet.addMenu('Azure Data Lake Storage Data', menuItems);
}

/*
 * Finds the first empty row in a spreadsheet by scanning an array of columns
 * @return The row number of the first empty row.
 */
function getFirstEmptyRowByColumnArray(spreadSheet, column) {
  var column = spreadSheet.getRange(column + ":" + column);
  var values = column.getValues(); // get all data in one call
  var ct = 0;
  while ( values[ct] && values[ct][0] != "" ) {
    ct++;
  }
  return (ct+1);
}

/*
 * Reads data from a specified 'table' and writes it to the specified sheet.
 *    (If the specified sheet does not exist, it is created.)
 */
function connectToADLSData() {
  var thisWorkbook = SpreadsheetApp.getActive();

  //select a sheet and create it if it does not exist
  var selectedSheet = Browser.inputBox('Which sheet would you like the data to post to?',Browser.Buttons.OK_CANCEL);
  if (selectedSheet == 'cancel')
    return;

  if (thisWorkbook.getSheetByName(selectedSheet) == null)
    thisWorkbook.insertSheet(selectedSheet);
  var resultSheet = thisWorkbook.getSheetByName(selectedSheet);
  var rowNum = 2;

  //select a Azure Data Lake Storage 'table'
  var table = Browser.inputBox('Which table would you like to pull data from?',Browser.Buttons.OK_CANCEL);
  if (table == 'cancel')
    return;

  var name = Jdbc.getConnection(dbUrl, {
    user: user, 
    password: userPwd
	}
  );

  //confirm that var table is a valid table/view
  var dbMetaData = name.getMetaData();
  var tableSet = dbMetaData.getTables(null, null, table, null);
  var validTable = false;
  while (tableSet.next()) {
    var tempTable = tableSet.getString(3);
    if (table.toUpperCase() == tempTable.toUpperCase()){
      table = tempTable;
      validTable = true;
      break;
    }
  } 
  tableSet.close();
  if (!validTable) {
    Browser.msgBox("Invalid table name: " + table, Browser.Buttons.OK);
    return;
  }

  var stmt = name.createStatement();

  var results = stmt.executeQuery('SELECT * FROM ' + table);
  var rsmd = results.getMetaData();
  var numCols = rsmd.getColumnCount();

  //if the sheet is empty, populate the first row with the headers
  var firstEmptyRow = getFirstEmptyRowByColumnArray(resultSheet, "A");
  if (firstEmptyRow == 1) {
    //collect column names
    var headers = new Array(new Array(numCols));
    for (var col = 0; col < numCols; col++){
      headers[0][col] = rsmd.getColumnName(col+1);
    }
    resultSheet.getRange(1, 1, headers.length, headers[0].length).setValues(headers);
  } else {
    rowNum = firstEmptyRow;
  }

  //write rows of Azure Data Lake Storage data to the sheet
  var values = new Array(new Array(numCols));
  while (results.next()) {
    for (var col = 0; col < numCols; col++) {
      values[0][col] = results.getString(col + 1);
    }
    resultSheet.getRange(rowNum, 1, 1, numCols).setValues(values);
    rowNum++;
  }

  results.close();
  stmt.close();
}