ElasticSearch Connector for Informatica

In this article you will learn how to integrate ElasticSearch data in Informatica 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 Informatica. Follow the steps below to see how we would accomplish that.

Download Documentation

Connect to ElasticSearch in other apps
ElasticSearch Connector Connect ElasticSearch in SSIS SSIS
Connect to ElasticSearch in SSIS
ElasticSearch Connector Connect ElasticSearch in SQL Server SQL Server
Connect to ElasticSearch in SQL Server
ElasticSearch Connector Connect ElasticSearch in Power BI Power BI
Connect to ElasticSearch in Power BI
ElasticSearch Connector Connect ElasticSearch in SSRS SSRS
Connect to ElasticSearch in SSRS
ElasticSearch Connector Connect ElasticSearch in MS Access MS Access
Connect to ElasticSearch in MS Access
ElasticSearch Connector Connect ElasticSearch in MS Excel MS Excel
Connect to ElasticSearch in MS Excel
ElasticSearch Connector Connect ElasticSearch in SSAS SSAS
Connect to ElasticSearch in SSAS
ElasticSearch Connector Connect ElasticSearch in C# C#
Connect to ElasticSearch in C#
ElasticSearch Connector Connect ElasticSearch in Python Python
Connect to ElasticSearch in Python
ElasticSearch Connector Connect ElasticSearch in JAVA JAVA
Connect to ElasticSearch in JAVA
ElasticSearch Connector Connect ElasticSearch in Tableau Tableau
Connect to ElasticSearch in Tableau
ElasticSearch Connector Connect ElasticSearch in SAP Crystal Reports SAP Crystal Reports
Connect to ElasticSearch in SAP Crystal Reports
ElasticSearch Connector Connect ElasticSearch in Azure Data Factory (Pipeline) Azure Data Factory (Pipeline)
Connect to ElasticSearch in Azure Data Factory (Pipeline)
ElasticSearch Connector Connect ElasticSearch in Azure Data Factory (SSIS) Azure Data Factory (SSIS)
Connect to ElasticSearch in Azure Data Factory (SSIS)
ElasticSearch Connector Connect ElasticSearch in Talend Studio Talend Studio
Connect to ElasticSearch in Talend Studio
ElasticSearch Connector Connect ElasticSearch in UiPath UiPath
Connect to ElasticSearch in UiPath
ElasticSearch Connector Connect ElasticSearch in PowerShell PowerShell
Connect to ElasticSearch in PowerShell
ElasticSearch Connector Connect ElasticSearch in ODBC ODBC
Connect to ElasticSearch in ODBC
NOTE: If you need to consume API which is not listed on connector library page then please refer to the below article links. It talks about how to read / write pretty much any API and not just ElasticSearch API. It explains various API tips / tricks using our other Universal Drivers not mentioned in this article (i.e. ZappySys JSON / XML and CSV Drivers).
How to read API data in Informatica (Call JSON / XML SOAP Service)
How to write data to API (POST) in Informatica (Call JSON / XML SOAP Service)

Introduction

Informatica PowerCenter LogoJSON / REST API is becoming more and more popular each day as everyone embrace cloud-centric services. This article is primarily focused on Informatica users who want to access ElasticSearch data or may be other API Integration in Informatica. However many tips and techniques described in this article will help you to understand how to integrate ElasticSearch / XML SOAP / JSON / REST API in other ETL / Reporting apps such as Tableau, Power BI, SSRS, Talend, Excel and many more.

After going through this article you will learn how to Read ElasticSearch / JSON / REST API data in Informatica and understand the concept of JSON / REST API. We will go through many screenshots and step-by-step examples to demonstrate  ElasticSearch or REST API integration in Informatica PowerCenter.

XML / JSON can come from a local file or REST API service (internal or public) so we will include both examples in this article (i.e. Read JSON files in Informatica,  Import REST API in Informatica). So let’s get started. Next article will focus on how to write data to API in Informatica (POST / PUT data)

Requirements

This article assumes that you have full filled following basic requirements.

  1. Download Install ZappySys ODBC PowerPack (API Driver for ElasticSearch included)
  2. Install Informatica PowerCenter Client Tools (e.g. Workflow and Mapping Designers)
  3. Access to a Relational database such as SQL Server (or use any of your choice e.g. Oracle, MySQL, DB2 ). If nothing available then you can use flat file target.

High level Steps for Import ElasticSearch data using Informatica (Read ElasticSearch API data)

Before we dive deep to learn how to load ElasticSearch data in Informatica (i.e. ElasticSearch to SQL Table), Here the summary of high-level steps you need to perform to import ElasticSearch in Informatica (same steps for Import JSON / XML / REST API).

  1. Download and Install ZappySys API Driver (for connecting to ElasticSearch)
  2. Create ODBC DSN using ZappySys API driver and choose ElasticSearch Connector during Wizard
  3. Create Relational > ODBC Connection in Informatica Workflow designer (Point to DSN we created in the previous step)
  4. Import ElasticSearch Source Definition in the Informatica Mapping Designer > Sources Tab
  5. Import Target Table Definition in the Informatica Mapping Designer > Targets Tab
  6. Create source to target mapping in Mappings tab
  7. Save mapping (name m_API_to_SQL_Load )
  8. Create Session using the mapping we created in the previous step
  9. Save Workflow and execute to load ElasticSearch data into SQL Table. Verify your data and log.
    Loading JSON data to SQL Table in Informatica (Import ElasticSearch / REST API / JSON Files)

    Loading ElasticSearch data to SQL Table in Informatica (Import REST API or JSON Files)

Video Tutorial – Read any API / JSON data in Informatica (Load ElasticSearch to SQL Table)

Below video is not about ElasticSearch API but its showing API access in general (for any API). By watching following ~5 min video can learn steps listed in this article to load JSON API data into SQL Server Table using ZappySys JSON Driver. You can go though full article to learn many useful details not covered in this video.

Getting Started – Import ElasticSearch to SQL Server in Informatica

Now let’s get started. For example purpose, we will read data from ElasticSearch and load data into SQL Server Table using Informatica Workflow.

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

Step-by-step instructions

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

  1. Install ZappySys ODBC PowerPack.

  2. Open ODBC Data Sources (x64):
    Open ODBC Data Source

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

    ZappySys API Driver
    Create new User DSN for 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
    ODBC DSN Template Selection

  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...
    ODBC DSN HTTP Connection Configuration

     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...
    ODBC DSN HTTP Connection Configuration

  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:
    ODBC ZappySys Data Source Preview

  7. Click OK to finish creating the data source.

Video instructions

Create Connection in Informatica Workflow Designer

Once you create DSN using API Driver our next step is to define a connection for ElasticSearch source in Informatica PowerCenter Workflow designer.

  1. Open Workflow designer [W] icon
  2. Goto Connections > Relational
    Create new connection for JSON in Informatica

    Create a new connection for ElasticSearch in Informatica

  3. Click New and select ODBC
    Select ODBC connection type in Informatica (Using ZappySys JSON ODBC DSN)

    Select ODBC connection type in Informatica (Using ZappySys API ODBC DSN)

  4. Now on the ODBC connection setup enter connection name, some fake userid / password (this is a required field but its ignored by JSON Driver)
  5. In the Connection String field enter the exact same name of DSN (Open ODBC Data Sources UI to confirm)
    Configure ElasticSearch connection in Informatica for REST API – Using ZappySys API ODBC Driver

    Configure ElasticSearch connection in Informatica for REST API – Using ZappySys API Driver

  6. Click OK to close the connection properties.

That’s it. Now we ready to move to next step (define source and target in Mapping Designer).

Import ElasticSearch Source Definition in Informatica Mapping Designer

Now let’s look at steps to import ElasticSearch table definition.

  1. Open Informatica Mapping Designer (Click [D] icon)
  2. Click on Source Icon to switch to Sources designer
  3. From the top menu > Click on Sources > Import from Database …
    Import JSON Source definition in Informatica Mapping Designer (JSON file or REST API)

    Import ElasticSearch Source definition in Informatica Mapping Designer (JSON file or REST API)

  4. Select ODBC data source from the dropdown (Find out DSN we created earlier to use as JSON Source)
  5. Click Connect button to get a list of tables. Any array node is listed as a table. Also, you will see array node with parent columns (e.g. value_with_parent). You may get some warning like below but they are harmless so just ignore by clicking OK.
    DLL name entry missing from C:\Informatica\PowerCenter8.6.1\client\bin\powrmart.ini Section = ODBCDLL Entry = ZappySys JSON Driver
    —————————————————-
    Using EXTODBC.DLL to support ZappySys JSON Driver. For native support of ZappySys JSON Driver make an entry in the .ini file.
    Select JSON Source Table in Informatica Mapping Designer (JSON file or REST API)

    Select ElasticSearch Source Table in Informatica Mapping Designer (JSON file or REST API)

  6. Select Table you wish to get (You can filter rows by custom SQL query. We will see later in this article how to do)
  7. Optionally once table structure is imported you can rename it
    Rename imported table definition in Informatica Source Designer

    Rename imported table definition in Informatica Source Designer

  8. That’s it, we are now ready to perform similar steps to import Target table structure in the next section.

Import SQL Server Target Definition in Informatica Mapping Designer

Now let’s look at steps to import Target table definition (very similar to the previous section, the only difference is this time we will select DSN which points to SQL Server or any other Target Server).

Now lets look at steps to import target table definition in Informatica mapping designer.

  1. In the Mapping Designer, Click on Target Icon to switch to Target designer
  2. From the top menu > Click on Targets > Import from Database …
  3. Select DSN for your Target server (if DSN doesn’t exist then create one by opening ODBC Sources just like we created one for JSON API source (see the previous section about creating DSN).
    Import target Table Definition in informatica

    Import target Table Definition in informatica

  4. Enter your userid , password and Schema name and click Connect to see tables
  5. Select Table name to and click OK import definition.
    Import Target SQL Table Definition in Informatica - Select table from the list

    Import Target SQL Table Definition in Informatica – Select table from the list

Create Source to Target Mapping in Informatica (Import JSON to SQL Server)

Once you have imported source and target table definition, we can create mapping and transformation to load data from JSON to SQL Table.

  1. First open Mapping Designer (Click [D] icon)
  2. Drag JSON Source from sources folder
  3. Drag SQL Table from Targets folder
  4. Map desired columns from Source to target
    Define Source to Target mapping for JSON to SQL Table load in Informatica

    Define Source to Target mapping for ElasticSearch to SQL Table load in Informatica

  5. For certain columns you may have to do datatype conversion. For example to convert OrderDate form nstring to DataTime you have to use Expression Transform like below and map it to target. In below example, our JSON has date format (e.g. 2018-01-31 12:00:00 AM ). To import this to DateTime field in SQL server we need to convert it using TO_DATE function. Use double quotes around T to make this format working.
    TO_DATE(OrderDate,'YYYY-MM-DD H12:MI:SS AM')

 --For ISO use below way
                TO_DATE(OrderDate,'YYYY-MM-DD"T"HH24:MI:SS')
    Informatica JSON to SQL Table Mapping - Datatype conversion (nstring to datetime)

    Informatica ElasticSearch to SQL Table Mapping – Datatype conversion (nstring to datetime)

  6. Once you done with mapping save your mapping and name it (i.e. m_Api_To_SQL)
  7. Now lets move to next section to create workflow.

Create Workflow and Session in Informatica

Now the final step is to create a new workflow. Perform following steps to create workflow which with a session task to import JSON data into SQL table.

  1. Open workflow designer by click [W] icon.
  2. Launch new workflow creation wizard by click Workflow top menu >  Wizard
    name your workflow (e.g. wf_Api_Tp_Sql_Table_Import)

    Creating Informatica Workflow - Wizard UI (Import JSON data to SQL Table)

    Creating Informatica Workflow – Wizard UI (Import ElasticSearch data to SQL Table)

  3. Finish the wizard and double-click the Session to edit some default properties.
  4. First change Error settings so we fail session on error (By default its always green)
    Fail Informatica Session on error (JSON to SQL Load)

    Fail Informatica Session on error (ElasticSearch data to SQL Load)

  5. Select JSON connection for Source
    Select JSON Source Connection in Informatica - JSON File / REST API Load to SQL Table

    Select ElasticSearch Source Connection in Informatica – Load ElasticSearch data to SQL Table

  6. Change default Source query if needed. You can pass parameters to this query to make it dynamic.
    Modify JSON Source SQL query - Pass parameters, change URL, set filter etc

    Modify ElasticSearch Source SQL query – Pass parameters, change URL, set filter etc

  7. Select Target connection of SQL Target Table
    Select SQL Target Connection in Informatica - JSON File / REST API Load to SQL Table

    Select SQL Target Connection in Informatica – Load ElasticSearch data to SQL Table

  8. Save workflow
  9. That’s it. We ready to run our first workflow to load JSON data to SQL.

Execute Workflow and Validate Log in Informatica

Now once you are done with your workflow, execute it to see the log.

Loading JSON data to SQL Table in Informatica (Import REST API or JSON Files)

Loading ElasticSearch data to SQL Table in Informatica (Import REST API or JSON Files)

 

POST data to ElasticSearch in Informatica

There will be a time when you like to send Source data to REST API or SOAP Web Service. You can use below Query for example. For detailed explanation on how to POST data in Informatica check this article.

Video Tutorial – How to POST data to REST API in Informatica

Here is detailed step by step video on REST API POST in informatica PowerCenter

 

Keywords

how to import ElasticSearch in informatica | how to read ElasticSearch data in informatica powercenter | how to test json from informatica | how to use ElasticSearch data as source in informatica power center | how to connect ElasticSearch in informatica 10 | informatica how to import data from ElasticSearch | informatica jtx to import ElasticSearch (use of java transformation) | informatica plugin for restful api using json | informatica power center and ElasticSearch support | informatica read ElasticSearch | informatica rest api | informatica ElasticSearch connector | json parser import informatica

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:
    ZappySys Driver - Add Stored Procedure

  2. Enter the desired Procedure name and click on OK:
    ZappySys Driver - Add Stored Procedure Name

  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>';

    ZappySys Driver - Create Custom Stored Procedure

  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';

    ZappySys Driver - Execute Custom Stored Procedure

  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''')

    ZappySys Driver - Generate SQL Server Query

  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.
    ZappySys Driver - Generate SQL Server Query

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:
    ZappySys Driver - Add Table

  2. Enter the desired Table name and click on OK:
    ZappySys Driver - Add Table Name

  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'

    ZappySys Driver - Create Custom Table

  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"

    ZappySys Driver - Execute Custom Virtual Table Query

  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''')

    ZappySys Driver - Generate SQL Server Query

  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.
    ZappySys Driver - Generate SQL Server Query

Actions supported by ElasticSearch Connector

ElasticSearch Connector support following actions for REST API integration. If some actions are not listed below then you can easily edit Connector file and enhance out of the box functionality.
 Create Index
Create a new index    [Read more...]
Parameter Description
New Index Name
 Delete Index
Delete an exising index    [Read more...]
Parameter Description
Index to delete
 List indexes
Lists indexes    [Read more...]
 List aliases
Lists aliases    [Read more...]
Parameter Description
 Get index metadata
Gets index metadata    [Read more...]
Parameter Description
Index Enter index name. If you set alias then select underlying alias Index here.
Alias
 Get documents from Index or Alias
Gets documents from Index or Alias    [Read more...]
 Get document by ID from Index or Alias
   [Read more...]
Parameter Description
Index Enter index name. If you set alias then select underlying alias Index here.
Alias
Enter Document ID
 Search / Query documents
Gets documents (Using JSON Query Language)    [Read more...]
 Count documents
   [Read more...]
Parameter Description
Index or Alias Name (choose one --OR-- enter * --OR-- comma seperated names) You can enter index name(s) for which you like to perform document count. Enter * (asterisk) to perform search across all indices or comma seperate list (i.e. myidx1,myidx2) or select one from the populated list.
Enter Query (JSON Format)
Option Value
All Records {"match_all": { } }
Record where comment or name contains TV word {"query_string": {"query": "comment:TV OR name:TV"} }
Record with comment field (attribute exists) {"query_string": {"query": "_exists_:comment"} }
 Insert documents
Insert documents    [Read more...]
Parameter Description
Index
Alias
 Update documents
Update documents    [Read more...]
Parameter Description
Index
Alias
 Upsert documents
Upserts documents    [Read more...]
Parameter Description
Index
Alias
 Delete documents
Deletes documents    [Read more...]
Parameter Description
Index
 Generic Request
This is generic endpoint. Use this endpoint when some actions are not implemented by connector. Just enter partial URL (Required), Body, Method, Header etc. Most parameters are optional except URL.    [Read more...]
Parameter Description
Url API URL goes here. You can enter full URL or Partial URL relative to Base URL. If it is full URL then domain name must be part of ServiceURL or part of TrustedDomains
Body Request Body content goes here
IsMultiPart Set this option if you want to upload file(s) (i.e. POST RAW file data) or send data using Multi-Part encoding method (i.e. Content-Type: multipart/form-data). Multi-Part request allows you to mix key/value and upload files in same request. On the other hand raw upload allows only single file upload (without any key/value) ==== Raw Upload (Content-Type: application/octet-stream) ===== To upload single file in raw mode check this option and specify full file path starting with @ sign in the Body (e.g. @c:\data\myfile.zip ) ==== Form-Data / Multipart Upload (Content-Type: multipart/form-data) ===== To treat your Request data as multi part fields you must specify key/value pairs separated by new lines into RequestData field (i.e. Body). Each key value pair is entered on new-line and key/value are separated using equal sign (=). Preceding and trailing spaces are ignored also blank lines are ignored. If field value has some any special character(s) then use escape sequence (e.g. For NewLine: \r\n, For Tab: \t, For at (@): \@). When value of any field starts with at sign (@) its automatically treated as File you want to upload. By default file content type is determined based on extension however you can supply content type manually for any field using this way [ YourFileFieldName.Content-Type=some-content-type ]. By default File Upload Field always includes Content-Type in the request (non file fields do not have content-type by default unless you supply manually). For some reason if you dont want to use Content-Type header in your request then supply blank Content-Type to exclude this header altogather [e.g. SomeFieldName.Content-Type= ]. In below example we have supplied Content-Type for file2 and SomeField1, all other fields are using default content-type. See below Example of uploading multiple files along with additional fields. If some API requires you to pass Content-Type: multipart/form-data rather than multipart/form-data then manually set Request Header => Content-Type: multipart/mixed (it must starts with multipart/ else will be ignored). file1=@c:\data\Myfile1.txt file2=@c:\data\Myfile2.json file2.Content-Type=application/json SomeField1=aaaaaaa SomeField1.Content-Type=text/plain SomeField2=12345 SomeFieldWithNewLineAndTab=This is line1\r\nThis is line2\r\nThis is \ttab \ttab \ttab SomeFieldStartingWithAtSign=\@MyTwitterHandle
Filter Enter filter to extract array from response. Example: $.rows[*] --OR-- $.customers[*].orders[*]. Check your response document and find out hierarchy you like to extract
Headers Headers for Request. To enter multiple headers use double pipe or new line after each {header-name}:{value} pair

ElasticSearch Connector Examples for Informatica 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.

Create a new index (i.e. Table)    [Read more...]

Create a new index (i.e. Create a new table). To trow error if table exists you can set ContineOnErrorForStatusCode=0

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

Delete an exising index (i.e. Table)    [Read more...]

Delete an exising index. It it exists it will show status code 400

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

Generic API Call for ElasticSearch    [Read more...]

When EndPoint not defined and you like to call some API use this way. Below example shows how to call CREATE INDEX API generic way. See other generic API call examples.

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

List indexes    [Read more...]

Lists indexes

SELECT * FROM Indexes

Get index metadata    [Read more...]

Gets index metadata

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

Read ElasticSearch documents from Index (all or with filter)    [Read more...]

Gets documents by index name (i.e. Table name) or alias name (i.e. View name). Using WHERE clause invokes client side engine so try to avoid WHERE clause and use WITH clause QUERY attribute. Use search endpoint instead to invoke query.

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

Read ElasticSearch documents from Alias (all or with filter)    [Read more...]

Gets documents by index name (i.e. Table name) or alias name (i.e. View name). Using WHERE clause invokes client side engine so try to avoid WHERE clause and use WITH clause QUERY attribute. Use search endpoint instead to invoke query.

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

Search documents from Index using ElasticSearch Query language    [Read more...]

Below example shows how to search on a comment field for TV word anywhere in the text for Index named MyIndexOrAliasName (it can be index name or alias name). For more information on ElasticSearch Query expression check this link https://www.elastic.co/guide/en/elasticsearch/reference/6.8/query-dsl-match-query.html

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" } }')

Search documents from Alias using ElasticSearch Query language    [Read more...]

Below example shows how to search on Alias rather than Index name. Alias is build on index (consider like a view in RDBMS). This example filtes data from Alias with some condition in the Query Text. For more information on ElasticSearch Query expression check this link https://www.elastic.co/guide/en/elasticsearch/reference/6.8/query-dsl-match-query.html

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" } }')

Count ElasticSearch index documents using ElasticSearch Query language    [Read more...]

Below example shows how to get just count of documents from Index (single, multiple or all index). Optionally you can supply expression to filter. For more information on ElasticSearch Query expression check this link https://www.elastic.co/guide/en/elasticsearch/reference/6.8/query-dsl-match-query.html

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"

Count ElasticSearch alias documents using ElasticSearch Query language    [Read more...]

Below example shows how to get just count of documents from Alias (single, multiple or all alias). Optionally you can supply expression to filter. For more information on ElasticSearch Query expression check this link https://www.elastic.co/guide/en/elasticsearch/reference/6.8/query-dsl-match-query.html

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"

Using JSON Array / Value functions    [Read more...]

Below example shows how to select specific elements from value array or use JSON PATH expression to extract from document array

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 documents into index with _id autogenerated    [Read more...]

When you dont supply _id column value, ElasticSearch will generate it automatically for you.

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

Insert documents into index with your own _id    [Read more...]

Inserts documents into index with _id column. _id is string datatype so can be 

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

Insert documents using nested attribute and raw fragments (JSON sub-documents, arrays)    [Read more...]

This example produces JSON document like this {"_id": "some_auto_generated_id" , "Location": { "City" : "Atlanta" , "ZipCode" : "30060" },"ColorsArray ": ["Red", "Blue", "Green"],"SomeNestedDoc": { "Col1" : "aaa" , "Col2" : "bbb" , "Col2" : "ccc" }} . Notice that how Column name with Dot translated into nested Columns (i.e. City, ZipCode) and Prefix raw:: allowed to treat value as array or sub document.

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 raw document (_rawdoc_ usage)    [Read more...]

This example shows how to insert document(s) in a raw format. When you use column name _rawdoc_ then its treated as RAW body. Notice that we use @ before string literal in value. This allow to use escape sequence (in this case \n for new line).

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 documents in index    [Read more...]

Updates documents in index

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

Update raw document (_rawdoc_ usage)    [Read more...]

This example shows how to update document(s) in a raw format. When you use column name _rawdoc_ then its treated as RAW body. Notice that we use @ before string literal in value. This allow to use escape sequence (in this case \n for new line).

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 array or sub document    [Read more...]

This example shows how to update Array / nested Sub-document by adding raw:: prefix infront of column name to treat column as json fragment

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

Delete documents from index    [Read more...]

Deletes documents from index

DELETE MyIndex WHERE _id = 'A1234'

Conclusion

In this article we discussed how to connect to ElasticSearch in Informatica and integrate data without any coding. Click here to Download ElasticSearch Connector for Informatica and try yourself see how easy it is. If you still have any question(s) then ask here or simply click on live chat icon below and ask our expert (see bottom-right corner of this page).

Download ElasticSearch Connector for Informatica Documentation 

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Download ElasticSearch Connector for Informatica Documentation

  • How to connect ElasticSearch in Informatica?

  • How to get ElasticSearch data in Informatica?

  • How to read ElasticSearch data in Informatica?

  • How to load ElasticSearch data in Informatica?

  • How to import ElasticSearch data in Informatica?

  • How to pull ElasticSearch data in Informatica?

  • How to push data to ElasticSearch in Informatica?

  • How to write data to ElasticSearch in Informatica?

  • How to POST data to ElasticSearch in Informatica?

  • Call ElasticSearch API in Informatica

  • Consume ElasticSearch API in Informatica

  • ElasticSearch Informatica Automate

  • ElasticSearch Informatica Integration

  • Integration ElasticSearch in Informatica

  • Consume real-time ElasticSearch data in Informatica

  • Consume real-time ElasticSearch API data in Informatica

  • ElasticSearch ODBC Driver | ODBC Driver for ElasticSearch | ODBC ElasticSearch Driver | SSIS ElasticSearch Source | SSIS ElasticSearch Destination

  • Connect ElasticSearch in Informatica

  • Load ElasticSearch in Informatica

  • Load ElasticSearch data in Informatica

  • Read ElasticSearch data in Informatica

  • ElasticSearch API Call in Informatica