ElasticSearch Connector for PowerShell In this article you will learn how to integrate ElasticSearch data in PowerShell without coding in just a few clicks (live / bi-directional connection to ElasticSearch). Read / write ElasticSearch data inside your app; perform many ElasticSearch operations without coding, just use easy to use high performance API Connector for ElasticSearch. Using ElasticSearch Connector you will be able to connect, read, and write data from within PowerShell. Follow the steps below to see how we would accomplish that. Download Documentation The driver mentioned above is part of ODBC PowerPack which is a collection of high-performance Drivers for various API data source (i.e. REST API, JSON, XML, CSV, Amazon S3 and many more). Using familiar SQL query language you can make live connections and read/write data from API sources or JSON / XML / CSV Files inside SQL Server (T-SQL) or your favorite Reporting (i.e. Power BI, Tableau, Qlik, SSRS, MicroStrategy, Excel, MS Access), ETL Tools (i.e. Informatica, Talend, Pentaho, SSIS). You can also call our drivers from programming languages such as JAVA, C#, Python, PowerShell etc. If you are new to ODBC and ZappySys ODBC PowerPack then check the following links to get started. ODBC PowerPack - System Requirements and Installation Getting Started - Using ODBC PowerPack ODBC API Driver Help File

Connect to ElasticSearch in other apps Connect to ElasticSearch in SSIS Connect to ElasticSearch in SQL Server Connect to ElasticSearch in Power BI Connect to ElasticSearch in SSRS Connect to ElasticSearch in Informatica Connect to ElasticSearch in MS Access Connect to ElasticSearch in MS Excel Connect to ElasticSearch in SSAS Connect to ElasticSearch in C# Connect to ElasticSearch in Python Connect to ElasticSearch in JAVA Connect to ElasticSearch in Tableau Connect to ElasticSearch in SAP Crystal Reports Connect to ElasticSearch in Azure Data Factory (Pipeline) Connect to ElasticSearch in Azure Data Factory (SSIS) Connect to ElasticSearch in Talend Studio Connect to ElasticSearch in UiPath Connect to ElasticSearch in ODBC

Create ODBC Data Source (DSN) based on ZappySys API Driver

Step-by-step instructions

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

1. Install ZappySys ODBC PowerPack.

2. Open ODBC Data Sources (x64):
   

3. Create a User Data Source (User DSN) based on ZappySys API Driver

   ZappySys API Driver

   
   You should create a System DSN (instead of a User DSN) if the client application is launched under a Windows System Account, e.g. as a Windows Service. If the client application is 32-bit (x86) running with a System DSN, use ODBC Data Sources (32-bit) instead of the 64-bit version.

4. When the Configuration window appears give your data source a name if you haven't done that already, then select "ElasticSearch" from the list of Popular Connectors. If "ElasticSearch" is not present in the list, then click "Search Online" and download it. Then set the path to the location where you downloaded it. Finally, click Continue >> to proceed with configuring the DSN:

   ElasticSearchDSN

   ElasticSearch

   

5. Now it's time to configure the Connection Manager. Select Authentication Type, e.g. Token Authentication. Then select API Base URL (in most cases, the default one is the right one). More info is available in the Authentication section.

    Basic Authentication (UserId/Password) [Http]

   Fill in all required parameters and set optional parameters if needed:

   ElasticSearchDSN

   ElasticSearch

   Basic Authentication (UserId/Password) [Http]

   http://localhost:9200

   Required Parameters
   Optional Parameters
   UserName	Fill in the parameter...
   Password	Fill in the parameter...
   IgnoreSSLCertificateErrors	Fill in the parameter...

   

    Windows Authentication (No Password) [Http]

   Fill in all required parameters and set optional parameters if needed:

   ElasticSearchDSN

   ElasticSearch

   Windows Authentication (No Password) [Http]

   http://localhost:9200

   Required Parameters
   Optional Parameters
   IgnoreSSLCertificateErrors	Fill in the parameter...

   

6. Once the data source has been configured, you can preview data. Select the Preview tab and use settings similar to the following to preview data:
   

7. Click OK to finish creating the data source.

Video instructions

Read ElasticSearch data in PowerShell

Sometimes, you need to quickly access and work with your ElasticSearch 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 ElasticSearch 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. Then simply follow these instructions:
   "DSN=ElasticSearchDSN"

   

   For your convenience, here is the whole PowerShell script:

   # Configure connection string and query
   $connectionString = "DSN=ElasticSearchDSN"
   $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 ElasticSearch fields
       $line = $format -f ($row["CustomerId"], $row["CompanyName"], $row["Country"], $row["Phone"])
       Write-Host $line
   }
   

   Access specific ElasticSearch 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 ElasticSearch.
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=ElasticSearchDSN"

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

# Configure connection string and query
$connectionString = "DSN=ElasticSearchDSN"
$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 API Driver - ElasticSearch

   Read / write ElasticSearch data inside your app; perform many ElasticSearch operations without coding, just use easy to use high performance API Connector for ElasticSearch

   ElasticSearchDSN

   
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. It usually happens when API provider generates a very long Refresh Token when OAuth is at play. If it happens you use such API, you may get this error:

"Connection string exceeds maximum allowed length of 1024"

But there is a solution to this by storing the Refresh Token in a file instead of directly in ODBC connection string. Follow the steps below to achieve this.

1. Open your ODBC data source
2. Hit Advanced tab and enter a file path:
   

   ZappySys API Driver - ElasticSearch

   Read / write ElasticSearch data inside your app; perform many ElasticSearch operations without coding, just use easy to use high performance API Connector for ElasticSearch

   ElasticSearchDSN

   

   If you cannot find the Advanced tab, try looking for Click to Configure link in Properties tab, under URL text box. Click it, and then configure the file path in OAuth Grant Options tab.

3. Then click Copy settings button to copy a full connection string and paste it into your script.
4. Before using it we still have to shorten it manually like this:
5. Our troubles are over, now you should be able to execute the script with no problems.

Write ElasticSearch 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=ElasticSearchDSN"
$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

Advanced topics

Create Custom Stored Procedure in ZappySys Driver

You can create procedures to encapsulate custom logic and then only pass handful parameters rather than long SQL to execute your API call.

Steps to create Custom Stored Procedure in ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here

1. Go to Custom Objects Tab and Click on Add button and Select Add Procedure:
   

2. Enter the desired Procedure name and click on OK:
   

3. Select the created Stored Procedure and write the your desired stored procedure and Save it and it will create the custom stored procedure in the ZappySys Driver:
   Here is an example stored procedure for ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here
   

   CREATE PROCEDURE [usp_get_orders]
       @fromdate = '<<yyyy-MM-dd,FUN_TODAY>>'
    AS
       SELECT * FROM Orders where OrderDate >= '<@fromdate>';
   

   
   

4. That's it now go to Preview Tab and Execute your Stored Procedure using Exec Command. In this example it will extract the orders from the date 1996-01-01:
   

   Exec usp_get_orders '1996-01-01';

   
   

5. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC usp_get_orders @fromdate=''1996-07-30''')

   
   

6. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Create Custom Virtual Table in ZappySys Driver

ZappySys API Drivers support flexible Query language so you can override Default Properties you configured on Data Source such as URL, Body. This way you don't have to create multiple Data Sources if you like to read data from multiple EndPoints. However not every application support supplying custom SQL to driver so you can only select Table from list returned from driver.

If you're dealing with Microsoft Access and need to import data from an SQL query, it's important to note that Access doesn't allow direct import of SQL queries. Instead, you can create custom objects (Virtual Tables) to handle the import process.

Many applications like MS Access, Informatica Designer wont give you option to specify custom SQL when you import Objects. In such case Virtual Table is very useful. You can create many Virtual Tables on the same Data Source (e.g. If you have 50 URLs with slight variations you can create virtual tables with just URL as Parameter setting.

1. Go to Custom Objects Tab and Click on Add button and Select Add Table:
   

2. Enter the desired Table name and click on OK:
   

3. And it will open the New Query Window Click on Cancel to close that window and go to Custom Objects Tab.

4. Select the created table, Select Text Type AS SQL and write the your desired SQL Query and Save it and it will create the custom table in the ZappySys Driver:
   Here is an example SQL query for ZappySys Driver. You can insert Placeholders also. Read more about placeholders here
   

   SELECT
     "ShipCountry",
     "OrderID",
     "CustomerID",
     "EmployeeID",
     "OrderDate",
     "RequiredDate",
     "ShippedDate",
     "ShipVia",
     "Freight",
     "ShipName",
     "ShipAddress",
     "ShipCity",
     "ShipRegion",
     "ShipPostalCode"
   FROM "Orders"
   Where "ShipCountry"='USA'

   
   

5. That's it now go to Preview Tab and Execute your custom virtual table query. In this example it will extract the orders for the USA Shipping Country only:
   

   SELECT * FROM "vt__usa_orders_only"

   
   

6. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC [usp_get_orders] ''1996-01-01''')

   
   

7. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Actions supported by ElasticSearch Connector

ElasticSearch Connector Examples for PowerShell Connection

This page offers a collection of SQL examples designed for seamless integration with the ZappySys API ODBC Driver under ODBC Data Source (36/64) or ZappySys Data Gateway, enhancing your ability to connect and interact with Prebuilt Connectors effectively.

SELECT * FROM create_index WITH(Name='my_new_index_name', ContineOnErrorForStatusCode=1)

SELECT * FROM delete_index WITH(Name='my_index_name', ContineOn404Error=1 )

SELECT * FROM generic_request 
WITH(Url='/my_index_name'
	, RequestMethod='PUT'
--	, Body='{}'
--	, Headers='X-Hdr1:aaa || x-HDR2: bbb'
	, Meta='acknowledged:bool'
	)

SELECT * FROM Indexes

SELECT * FROM get_index_metadata WITH (Index='my_index_name')

SELECT * FROM MyIndexOrAliasName --WITH(Query='{"match": { "PartNumber" : "P50" } }')

SELECT * FROM MyIndexOrAliasName --WITH(Query='{"match": { "PartNumber" : "P50" } }')

SELECT * FROM MyIndexOrAliasName WITH(Query='{"match": { "comment" : "TV" } }')
		
		--or use below - slight faster (avoids table / alias list validation)
		--SELECT * FROM search WITH(Index='MyIndexName', Query='{"match": { "comment" : "TV" } }')
		--SELECT * FROM search WITH(Index='MyIndexName', Alias='MyAliasName', Query='{"match": { "comment" : "TV" } }')

SELECT * FROM MyAliasName WITH(Query='{"match": { "comment" : "TV" } }')
		
		--or use search endpoint then you must supply both Index name and Alias name 
		--calling /search endpoint in FROM clause is slight faster (avoids table / alias list validation)
		--SELECT * FROM search WITH(Index='MyIndexName',Index='MyAliasName', Query='{"match": { "comment" : "TV" } }')

SELECT * FROM count WITH(Index='MyIndexOrAliasName') --//get count of documents in index / alias named MyIndexOrAliasName
SELECT * FROM count WITH(Index='*') --//get count of documents in all indices (total distinct _id found across all indices + alias) 
SELECT * FROM count WITH(Index='MyIndex1,MyIndex2,MyAlias1,MyAlias2')--//get count of documents in indices named MyIndex1, MyIndex2 and Alias named MyAlias1,MyAlias2
SELECT * FROM count WITH(Index='MyIndexOrAliasName', Query='{"match": { "comment" : "TV" } }') --//get count of documents in MyIndex where comment field contains word "TV"

SELECT * FROM count WITH(Index='MyIndexOrAliasName') --//get count of documents in index / alias named MyIndexOrAliasName
SELECT * FROM count WITH(Index='*') --//get count of documents in all indices (total distinct _id found across all indices + alias)
SELECT * FROM count WITH(Index='MyIndexOrAlias1,MyIndexOrAlias2') --//get count of documents in MyIndex1 and MyIndex2
SELECT * FROM count WITH(Index='MyIndex', Query='{"match": { "comment" : "TV" } }') --//get count of documents in Index named MyIndex where comment field contains word "TV"
SELECT * FROM count WITH(Index='MyAlias', Query='{"match": { "comment" : "TV" } }') --//get count of documents in Alias named MyAlias where comment field contains word "TV"

SELECT _id
        , JSON_ARRAY_FIRST(colors) as first_color
        , JSON_ARRAY_LAST(colors) as last_color
        , JSON_ARRAY_NTH(colors,3) as third_color
        , JSON_VALUE(locationList,'$.locationList[0].country') as first_preferred_country
        , JSON_VALUE(locationList,'$.locationList[?(@country=='India')].capital as capital_of_india
FROM shop WHERE _Id='1'

INSERT INTO MyIndex([MyCol1], [MyCol2] ) VALUES (100, 'A1')

INSERT INTO MyIndex(_id, [MyCol1], [MyCol2] ) VALUES ('A1234', 100, 'A1')

INSERT INTO MyIndexName ([Location.City], [Location.ZipCode], [raw::ColorsArray], [raw::SomeNestedDoc] )
VALUES ('A1234', 'Atlanta', '30060', '["red","green","blue"]', '{"Col1":"aaa","Col2":"bbb","Col3":"ccc"}' )

INSERT INTO shop(_RAWDOC_) 
VALUES(@'{"create":{"_index":"shop","_id":"1"}}\n{"name":"record-1","colors":["yellow","orange"]}\n{"create":{"_index":"shop","_id":"2"}}\n{"name":"record-2","colors":["red","blue"]}\n')

UPDATE MyIndex
  SET Col1 = 'NewValue-1', Col2 = 'NewValue-2'
  WHERE _Id = 'A1234'

UPDATE shop SET _rawdoc_ = @'{"update": {"_index": "shop", "_id": "1"}}\n{ "doc": {"colors":["yellow","orange"] } }\n{"update": {"_index": "shop", "_id": "2"}}\n{ "doc": {"colors":["yellow","blue"] } }\n'

UPDATE MyIndex
  SET name = 'abcd', [raw::colors]='["yellow","red"]', [raw::location]='{x:10, y:20}' 
  WHERE _id='1'

DELETE MyIndex WHERE _id = 'A1234'

Conclusion

Download ElasticSearch Connector for PowerShell Documentation 

More integrations

Other application integration scenarios for ElasticSearch

SSIS

SQL Server

Power BI

SSRS

Informatica

MS Access

MS Excel

SSAS

C#

Python

JAVA

Tableau

SAP Crystal Reports

Azure Data Factory (Pipeline)

Azure Data Factory (SSIS)

Talend Studio

UiPath

ODBC

Other connectors for PowerShell

Amazon Ads

Amazon MWS

Azure DevOps

Cosmos DB

DropBox

ElasticSearch

FastSpring

Google BigQuery

Google Calendar

Google Drive

Google Sheets

Hubspot

Jira

Mailchimp

ManagedEngine ServiceDesk Plus (Zoho)

Nativo

OData

OneDrive

Outlook Mail (Office 365)

Power BI

ServiceNow

SharePoint Online

Shopify

Stripe

YouTube

Zendesk

Zoho CRM

Zoho SalesIQ

Zoom

REST API

JSON

JSON File

XML

SOAP

XML File

JDBC-ODBC Bridge

Salesforce

CSV

Amazon S3 JSON File

Amazon S3 XML File

Amazon S3 CSV File

Azure Blob JSON File

Azure Blob XML File

Azure Blob CSV File

FTP/SFTP JSON File

FTP/SFTP XML File

FTP/SFTP CSV File

Build your own Custom API Connector

Download ElasticSearch Connector for PowerShell Documentation

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