Idempotent filter with simple file
Download as pptx, pdf0 likes555 views
The document discusses how to use the Idempotent Filter in Mule to avoid duplicate messages. It demonstrates configuring the filter with simple-text-file-store to store unique IDs of messages in a text file and check for duplicates. Hitting a test URL the first time will return "passed" as the message is unique, but the second time it will return an exception as the message is now a duplicate.
1 of 10
Downloaded 11 times
Ad
Recommended
Converting with custom transformer
Converting with custom transformerF K This document discusses how to use a custom transformer in Mule to directly transform an XML payload to JSON. It provides an example of a Mule flow that uses a custom Java transformer class to take an XML file, convert it to a JSON string, and write the output to a new file. The custom transformer uses the Jackson XML and JSON libraries to perform the actual conversion between the two formats. Testing the flow results in the XML payload being successfully transformed to JSON and written out as expected.
Xslt in mule
Xslt in muleirfan1008 XSLT can be used to transform XML payloads in Mule applications. The document demonstrates setting an XML payload and using an XSLT transformer component with an XSLT file to transform the XML into a new format. The example Mule flow uses an HTTP inbound endpoint, sets an XML payload, and applies an XSLT transformation defined in a Transform.xslt file to output a new XML format.
Mule requesterdemo
Mule requesterdemoAnirban Sen Chowdhary The Mule Requester component allows messages to be retrieved from inbound endpoints like JMS queues or HTTP requests within a Mule flow. It is triggered by an HTTP request hitting a URL on the server. The Mule Requester then fetches a message from a JMS queue named "input" and the message payload is logged. The Mule Requester provides the ability to interact with inbound endpoints on-demand within the flow.
Mule xml transformation
Mule xml transformationD.Rajesh Kumar This document discusses how to transform an XML payload into a different XML format using XSLT in Mule. It provides an example of an input XML payload and desired output with an additional element. It then shows a Mule flow using an XSLT transformer to modify the input XML by adding the new element, with the value passed from a variable. Testing confirms the transformed XML payload is output as expected.
Xml to xml transformation in mule
Xml to xml transformation in mulemdfkhan625 This document discusses using XSLT to transform XML payloads in Mule applications. It provides an example of transforming an input XML payload containing name and id elements into an output XML payload that adds a designation element. The Mule flow uses an XSLT transformer to apply an XSL stylesheet to the input XML and output the transformed XML. Testing the flow by deploying the application and sending a request demonstrates how XSLT can easily modify XML payloads in Mule.
Xslt in mule
Xslt in muleMohammed246 The document discusses how to use XSLT transformations in Mule applications. XSLT can transform XML payloads from one form to another. Mule supports XSLT transformations using the XSLT transformer component. The example shows a flow that uses an HTTP inbound endpoint, sets an XML payload, applies an XSLT transformation defined in a file, and outputs the transformed XML. The XSLT file uses templates and XPath to map elements from the source XML to the new structure in the output XML.
Xslt with mule
Xslt with muleSon Nguyen XSLT is used to transform XML documents into other formats like other XML documents, HTML, text, etc. In Mule, the XSLT transformer component allows transforming XML payloads using XSLT. For example, an XML payload containing employee data can be transformed into a new XML format by applying an XSLT stylesheet file in the Mule flow.
Splitting with mule part2
Splitting with mule part2Anirban Sen Chowdhary Mule ESB can split a large message into smaller parts using a Splitter flow control component. This allows large messages containing repeating elements, like a list, to be broken into individual fragments that can then be processed separately. The document demonstrates using a Splitter to break up a JSON payload containing an array of "events" into separate logs of each event's ID and timestamp, handling the large list efficiently. Splitters are useful for processing large repeating data in XML or JSON payloads.
Xml to xml transformation in mule
Xml to xml transformation in muleRajkattamuri This document discusses how to transform an XML payload into another XML format using XSLT in Mule. It provides an example of taking an input XML payload with two elements, name and id, and transforming it to an output XML payload with an additional element, designation. The transformation is done with an XSLT file that is referenced in the Mule flow. The flow accepts the input XML, sets a designation variable, runs the payload through the XSLT transformer, and produces the transformed output XML payload.
Scatter and gather in mule
Scatter and gather in muleRajkattamuri Scatter-Gather in Mule allows sending a request message to multiple targets concurrently, collecting the responses from all routes and aggregating them into a single message. It implements this using message processors that process flows concurrently and then combine the payloads at the end. For example, a flow can contain two subflows that run concurrently using Scatter-Gather, with the responses from both subflows merged into a single payload.
Json to json transformation in mule
Json to json transformation in muleAntonio Pellegrino This document discusses how to transform a JSON payload into a different JSON format in Mule. It provides an example of transforming an input JSON with name and id fields into an output JSON that adds a designation field. The document recommends using an expression transformer to dynamically modify the input JSON and produce the transformed output JSON in Mule without needing the enterprise Datamapper component. It includes an example Mule flow that uses JSON transformers and set variables along with an expression transformer to transform one JSON payload into another with an additional field.
Mule ESB - How to convert from Xml to Json in 5 minutes
Mule ESB - How to convert from Xml to Json in 5 minutesGennaro Spagnoli This document discusses how to create an XML to JSON converter using Mule ESB in 5 minutes. It describes creating a simple HTTP listener flow to receive XML data, adding an XML to JSON transformer to convert the data, and logging the transformed JSON output to the console. The tutorial is tested by sending sample XML to the flow using Postman and verifying the JSON response.
Mulesoft http connector
Mulesoft http connectorkumar gaurav The document provides an overview of Mulesoft's HTTP Connector. It describes how the connector can be used to listen for and send HTTP/HTTPS requests. It also provides a sample use case demonstrating how to configure the connector as a listener to handle incoming GET requests, transforming the payload and logging the response.
Parameters as a part of body
Parameters as a part of bodyAnirban Sen Chowdhary The document discusses how to map inbound message properties in Mule to the message payload using the http:body-to-parameter-map-transformer. It explains that Mule messages have properties, payload, and attachments. Properties contain things like query parameters. The transformer allows moving properties, like query parameters, into the payload. An example shows query parameters in the properties, then using the transformer to put them in the payload instead. Checking the logs confirms the parameters are now in the payload after transforming.
xslt in mule
xslt in mulePraneethchampion XSLT is used to transform XML payloads between different forms. In Mule, the XSLT transformer component allows transforming XML payloads using XSLT stylesheets. For example, a flow uses an HTTP inbound endpoint, sets an XML payload, and applies an XSLT stylesheet using the XSLT transformer to output a new transformed XML payload. The XSLT stylesheet matches elements in the input XML and outputs a new structure defined in the stylesheet.
Mule message enricher
Mule message enricherAnirban Sen Chowdhary The Mule Message Enricher allows processing of the message without modifying the original payload. It provides a scope to add message processors that perform tasks like calling external services and extracting values from the response, without changing the original message. For example, a flow can use the enricher to call a web service, extract a value from the response into a variable, and log both the variable and original payload at the end, keeping the payload unchanged throughout.
Using XSLT in Mule
Using XSLT in MuleAnirban Sen Chowdhary XSLT (Extensible Stylesheet Language Transformations) is a language used to transform XML documents into other formats like other XML documents, HTML, text, etc. It can be used in Mule to transform an XML payload from one structure to another. For example, a Mule flow gets an XML payload, passes it through an XSLT transformer using an XSL stylesheet, which transforms the XML to a new structure and outputs the transformed XML payload.
Mapping and listing with mule
Mapping and listing with muleAnirban Sen Chowdhary This document discusses how to define list and map variables in Mule ESB. It shows that lists and maps can be defined as Mule variables by using square brackets and curly braces. Values can then be retrieved from the lists and maps using indexes and keys. Examples are provided to demonstrate defining a list variable, retrieving values from the list, defining a map variable, and retrieving values from the map. The document also includes an example Mule configuration that reassigns list values and logs the new list values.
Idempotent filter in Mule
Idempotent filter in MuleF K The document discusses how to use an Idempotent Filter in Mule to avoid duplicate messages by checking message IDs. It provides an example of configuring an Idempotent Filter to use a simple-text-file-store to store message IDs in files and check for duplicates. When the example flow is run, it generates a text file to store message IDs and will return "passed" for new messages but "EXCEPTION" for duplicate messages.
Mapping and listing with mule
Mapping and listing with mulePraneethchampion Mule ESB allows defining variables to store data, including flow and session variables. Lists and maps can be defined as Mule variables similarly to Java by using square brackets. Values can then be retrieved from the list or map using indexes or keys, and the list values can be reassigned. For example, a list variable can be set as #[{1000,100,14,1}] and values retrieved using flowVars['test'][0]. Similarly, a map can be set as # [{'k2':'new', 'k3':'v3'}] and values retrieved using flowVars['customMap']['k2'].
RAMLing around with mule part2
RAMLing around with mule part2Anirban Sen Chowdhary The document discusses ensuring the Mocking service button is turned off to avoid creating a mock URL. It notes that the RAML file will be downloaded as a zip file locally, and this file needs to be extracted to access and use the generated .raml file.
Mule MMC as a service
Mule MMC as a serviceAnirban Sen Chowdhary This presentation represent a demonstration on the various apis that the Mule MMC expose. Using this apis, we can perform various functionalities of Mule MMC portal like creating application, deploying, undeploying, deleting application etc.
Accessing Mule variables in groovy
Accessing Mule variables in groovyAnirban Sen Chowdhary This document discusses how to access variables in Groovy scripts and Java code within Mule applications. There are two types of variables in Mule: flow variables, which are limited to a specific flow, and session variables, which are global to the entire application. The document provides examples of how to retrieve variable values using different methods like getInvocationProperty() and getSessionProperty() in Groovy, and set variables using setProperty() and setSessionProperty(). It demonstrates retrieving variables set in a Mule flow and also setting variables in Groovy scripts to be accessed in flows.
Encrypting/Decrypting mule
Encrypting/Decrypting muleAnirban Sen Chowdhary 1) The document discusses using base64 encoding and decoding transformers in Mule to encrypt and decrypt file payloads.
2) It provides an example Mule flow that uses a base64 encoder transformer to encrypt a file, and another flow using a base64 decoder transformer to decrypt the file back to its original contents.
3) The example demonstrates picking up a file, encrypting it with base64 encoding, writing it to a new location, then decrypting and writing the original file contents back with base64 decoding.
Calling database with groovy in mule
Calling database with groovy in muleAnirban Sen Chowdhary The document discusses using Groovy scripts with Mule's JDBC connector to perform CRUD operations on a SQL database table. It shows how to configure the JDBC connector, define a simple Mule flow, and write Groovy scripts that use the connector to query and retrieve data from the table based on a request parameter, and to delete a row from the table. The Groovy scripts demonstrate executing SQL queries using parameters and handling the response.
Mule with stored procedure
Mule with stored procedureAnirban Sen Chowdhary This document discusses a simple yet amazing trick in MuleSoft that involves using a stored procedure. It provides a link to a post that further explains how to perform this trick in MuleSoft using a stored procedure. The trick allows integrating MuleSoft with databases in an effective manner.
RAMLing around with mule
RAMLing around with muleAnirban Sen Chowdhary It describe the RAML technology in creating, designing and testing a RESTful api.
Using spring task scheduler in java in mule
Using spring task scheduler in java in muleAnirban Sen Chowdhary This document discusses how to schedule tasks and monitor events in a Mule application using Java classes and the Spring task scheduler rather than the Quartz scheduler or Poll component. It provides an example of a simple Java class that logs a message every 10 seconds, and the Spring configuration that schedules the class to run repeatedly. When the Mule flow is triggered from a browser, it logs a message and the scheduled Java class also logs a message every 10 seconds in the console.
Designing rest with raml
Designing rest with ramlAnirban Sen Chowdhary This presentation describe the creation of a RESTful api using RAML. It describe various specs of RAML
More Related Content
What's hot (12)
Xml to xml transformation in mule
Xml to xml transformation in muleRajkattamuri This document discusses how to transform an XML payload into another XML format using XSLT in Mule. It provides an example of taking an input XML payload with two elements, name and id, and transforming it to an output XML payload with an additional element, designation. The transformation is done with an XSLT file that is referenced in the Mule flow. The flow accepts the input XML, sets a designation variable, runs the payload through the XSLT transformer, and produces the transformed output XML payload.
Scatter and gather in mule
Scatter and gather in muleRajkattamuri Scatter-Gather in Mule allows sending a request message to multiple targets concurrently, collecting the responses from all routes and aggregating them into a single message. It implements this using message processors that process flows concurrently and then combine the payloads at the end. For example, a flow can contain two subflows that run concurrently using Scatter-Gather, with the responses from both subflows merged into a single payload.
Json to json transformation in mule
Json to json transformation in muleAntonio Pellegrino This document discusses how to transform a JSON payload into a different JSON format in Mule. It provides an example of transforming an input JSON with name and id fields into an output JSON that adds a designation field. The document recommends using an expression transformer to dynamically modify the input JSON and produce the transformed output JSON in Mule without needing the enterprise Datamapper component. It includes an example Mule flow that uses JSON transformers and set variables along with an expression transformer to transform one JSON payload into another with an additional field.
Mule ESB - How to convert from Xml to Json in 5 minutes
Mule ESB - How to convert from Xml to Json in 5 minutesGennaro Spagnoli This document discusses how to create an XML to JSON converter using Mule ESB in 5 minutes. It describes creating a simple HTTP listener flow to receive XML data, adding an XML to JSON transformer to convert the data, and logging the transformed JSON output to the console. The tutorial is tested by sending sample XML to the flow using Postman and verifying the JSON response.
Mulesoft http connector
Mulesoft http connectorkumar gaurav The document provides an overview of Mulesoft's HTTP Connector. It describes how the connector can be used to listen for and send HTTP/HTTPS requests. It also provides a sample use case demonstrating how to configure the connector as a listener to handle incoming GET requests, transforming the payload and logging the response.
Parameters as a part of body
Parameters as a part of bodyAnirban Sen Chowdhary The document discusses how to map inbound message properties in Mule to the message payload using the http:body-to-parameter-map-transformer. It explains that Mule messages have properties, payload, and attachments. Properties contain things like query parameters. The transformer allows moving properties, like query parameters, into the payload. An example shows query parameters in the properties, then using the transformer to put them in the payload instead. Checking the logs confirms the parameters are now in the payload after transforming.
xslt in mule
xslt in mulePraneethchampion XSLT is used to transform XML payloads between different forms. In Mule, the XSLT transformer component allows transforming XML payloads using XSLT stylesheets. For example, a flow uses an HTTP inbound endpoint, sets an XML payload, and applies an XSLT stylesheet using the XSLT transformer to output a new transformed XML payload. The XSLT stylesheet matches elements in the input XML and outputs a new structure defined in the stylesheet.
Mule message enricher
Mule message enricherAnirban Sen Chowdhary The Mule Message Enricher allows processing of the message without modifying the original payload. It provides a scope to add message processors that perform tasks like calling external services and extracting values from the response, without changing the original message. For example, a flow can use the enricher to call a web service, extract a value from the response into a variable, and log both the variable and original payload at the end, keeping the payload unchanged throughout.
Using XSLT in Mule
Using XSLT in MuleAnirban Sen Chowdhary XSLT (Extensible Stylesheet Language Transformations) is a language used to transform XML documents into other formats like other XML documents, HTML, text, etc. It can be used in Mule to transform an XML payload from one structure to another. For example, a Mule flow gets an XML payload, passes it through an XSLT transformer using an XSL stylesheet, which transforms the XML to a new structure and outputs the transformed XML payload.
Mapping and listing with mule
Mapping and listing with muleAnirban Sen Chowdhary This document discusses how to define list and map variables in Mule ESB. It shows that lists and maps can be defined as Mule variables by using square brackets and curly braces. Values can then be retrieved from the lists and maps using indexes and keys. Examples are provided to demonstrate defining a list variable, retrieving values from the list, defining a map variable, and retrieving values from the map. The document also includes an example Mule configuration that reassigns list values and logs the new list values.
Idempotent filter in Mule
Idempotent filter in MuleF K The document discusses how to use an Idempotent Filter in Mule to avoid duplicate messages by checking message IDs. It provides an example of configuring an Idempotent Filter to use a simple-text-file-store to store message IDs in files and check for duplicates. When the example flow is run, it generates a text file to store message IDs and will return "passed" for new messages but "EXCEPTION" for duplicate messages.
Mapping and listing with mule
Mapping and listing with mulePraneethchampion Mule ESB allows defining variables to store data, including flow and session variables. Lists and maps can be defined as Mule variables similarly to Java by using square brackets. Values can then be retrieved from the list or map using indexes or keys, and the list values can be reassigned. For example, a list variable can be set as #[{1000,100,14,1}] and values retrieved using flowVars['test'][0]. Similarly, a map can be set as # [{'k2':'new', 'k3':'v3'}] and values retrieved using flowVars['customMap']['k2'].
Viewers also liked (15)
RAMLing around with mule part2
RAMLing around with mule part2Anirban Sen Chowdhary The document discusses ensuring the Mocking service button is turned off to avoid creating a mock URL. It notes that the RAML file will be downloaded as a zip file locally, and this file needs to be extracted to access and use the generated .raml file.
Mule MMC as a service
Mule MMC as a serviceAnirban Sen Chowdhary This presentation represent a demonstration on the various apis that the Mule MMC expose. Using this apis, we can perform various functionalities of Mule MMC portal like creating application, deploying, undeploying, deleting application etc.
Accessing Mule variables in groovy
Accessing Mule variables in groovyAnirban Sen Chowdhary This document discusses how to access variables in Groovy scripts and Java code within Mule applications. There are two types of variables in Mule: flow variables, which are limited to a specific flow, and session variables, which are global to the entire application. The document provides examples of how to retrieve variable values using different methods like getInvocationProperty() and getSessionProperty() in Groovy, and set variables using setProperty() and setSessionProperty(). It demonstrates retrieving variables set in a Mule flow and also setting variables in Groovy scripts to be accessed in flows.
Encrypting/Decrypting mule
Encrypting/Decrypting muleAnirban Sen Chowdhary 1) The document discusses using base64 encoding and decoding transformers in Mule to encrypt and decrypt file payloads.
2) It provides an example Mule flow that uses a base64 encoder transformer to encrypt a file, and another flow using a base64 decoder transformer to decrypt the file back to its original contents.
3) The example demonstrates picking up a file, encrypting it with base64 encoding, writing it to a new location, then decrypting and writing the original file contents back with base64 decoding.
Calling database with groovy in mule
Calling database with groovy in muleAnirban Sen Chowdhary The document discusses using Groovy scripts with Mule's JDBC connector to perform CRUD operations on a SQL database table. It shows how to configure the JDBC connector, define a simple Mule flow, and write Groovy scripts that use the connector to query and retrieve data from the table based on a request parameter, and to delete a row from the table. The Groovy scripts demonstrate executing SQL queries using parameters and handling the response.
Mule with stored procedure
Mule with stored procedureAnirban Sen Chowdhary This document discusses a simple yet amazing trick in MuleSoft that involves using a stored procedure. It provides a link to a post that further explains how to perform this trick in MuleSoft using a stored procedure. The trick allows integrating MuleSoft with databases in an effective manner.
RAMLing around with mule
RAMLing around with muleAnirban Sen Chowdhary It describe the RAML technology in creating, designing and testing a RESTful api.
Using spring task scheduler in java in mule
Using spring task scheduler in java in muleAnirban Sen Chowdhary This document discusses how to schedule tasks and monitor events in a Mule application using Java classes and the Spring task scheduler rather than the Quartz scheduler or Poll component. It provides an example of a simple Java class that logs a message every 10 seconds, and the Spring configuration that schedules the class to run repeatedly. When the Mule flow is triggered from a browser, it logs a message and the scheduled Java class also logs a message every 10 seconds in the console.
Designing rest with raml
Designing rest with ramlAnirban Sen Chowdhary This presentation describe the creation of a RESTful api using RAML. It describe various specs of RAML
Xml to xml transformation in mule
Xml to xml transformation in muleAnirban Sen Chowdhary This document discusses a simple yet amazing trick for transforming XML to XML in Mule. It demonstrates how to take an XML payload and transform it to a new XML structure without writing any complex transformation logic. The full post with more details on this XML transformation technique in Mule can be found at a specific URL.
VM example in mule
VM example in muleAnirban Sen Chowdhary The document discusses decomposing a complex Mule flow into smaller parts connected by VM components when exposing a CXF web service. Some key advantages of this approach are better control over each event, reduced complexity, and improved performance compared to other queue services. An example is provided of a flow broken into two parts - one for the CXF component and one for the implementation class, connected by a VM queue. Properties are stored before sending to the VM to preserve them across flows.
Getting anypoint studios all versions
Getting anypoint studios all versionsAnirban Sen Chowdhary Anypoint Studio is a graphical design environment for Anypoint Platform that allows developers to create SOA, SaaS, and API integrations with a single click deployment to Mule runtime on-premises or in the cloud. To use Anypoint Studio, Java SE JDK 7 or 8 must be installed. Previous versions of Anypoint Studio, formerly known as Mule Studio, can be downloaded from a URL listing all releases by appending the version key to the download URL.
Simple groovy example in mule
Simple groovy example in muleAnirban Sen Chowdhary This document shows how to use a Groovy scripting component to hold a Mule flow for a period of time before processing the payload. The Groovy component uses the sleep method to pause the flow for 3000 milliseconds. This holds the file payload before writing it to the outbound location. The example flow uses a file inbound endpoint to pick up a file, passes it to the Groovy component which sleeps for 3 seconds, and then writes the file to the outbound location. This allows dynamically pausing a flow to hold the payload for a specified interval of time.
Ad
Similar to Idempotent filter with simple file (20)
Idempotent filter in mule
Idempotent filter in muleMohammed246 The document discusses how the Idempotent Filter in Mule ensures only unique messages are received by checking message IDs. It demonstrates configuring the Idempotent Filter with a simple-text-file-store to avoid duplicate messages. When messages are received, the filter will check the file store for duplicates and only allow unique messages to pass through the flow.
Idempotent filter with mule
Idempotent filter with muleSon Nguyen The document discusses the Idempotent Filter in Mule, which checks the unique ID of incoming messages to ensure only unique messages are received by a service. It demonstrates configuring the Idempotent Filter with a simple-text-file-store, which stores all messages in a file and checks for duplicates. Hitting the same URL twice shows the first pass succeeds and the second fails, demonstrating the filter preventing duplicate messages.
Idempotent filter in mule
Idempotent filter in mulePraneethchampion The document discusses how to use an Idempotent Filter in Mule to avoid duplicate messages by checking message IDs. It provides an example of configuring an Idempotent Filter to use a simple-text-file-store to store message IDs in files and check for duplicates. When the example flow is run, it generates a text file to store message IDs and will return "passed" for new messages but "EXCEPTION" for duplicate messages.
Idempotent filter with simple file
Idempotent filter with simple fileAbdulImrankhan7 The document discusses how to use an Idempotent Filter in Mule to avoid duplicate messages by checking message IDs. It provides an example of configuring an Idempotent Filter to use a simple-text-file-store to store message IDs in files and check for duplicates. When the example flow is run, it generates a text file to store message IDs and will return "passed" for new messages but "EXCEPTION" for duplicate messages.
Idempotent filter with simple file
Idempotent filter with simple fileHasan Syed The document discusses how to use an Idempotent Filter in Mule to avoid duplicate messages by checking message IDs. It provides an example of configuring an Idempotent Filter to use a simple-text-file-store to store message IDs in files and check for duplicates. When the example flow is run, it generates a text file to store message IDs and will return "passed" for new messages but "EXCEPTION" for duplicate messages.
Idempotent filter with simple file
Idempotent filter with simple fileKhan625 The document discusses how to use an Idempotent Filter in Mule to avoid duplicate messages by checking message IDs. It provides an example of configuring an Idempotent Filter to use a simple-text-file-store to store message IDs in files and check for duplicates. When the example flow is run, it generates a text file to store message IDs and will return "passed" for new messages but "EXCEPTION" for duplicate messages.
Idempotent filter with simple file
Idempotent filter with simple fileSunil Komarapu The document discusses how to use an Idempotent Filter in Mule to avoid duplicate messages by checking message IDs. It provides an example of configuring an Idempotent Filter to use a simple-text-file-store to store message IDs in files and check for duplicates. When the example flow is run, it generates a text file to store message IDs and will return "passed" for new messages but "EXCEPTION" for duplicate messages.
Idempotent filter with simple file
Idempotent filter with simple filemdfkhan625 The document discusses how to use an Idempotent Filter in Mule to avoid duplicate messages by checking message IDs. It provides an example of configuring an Idempotent Filter to use a simple-text-file-store to store message IDs in files and check for duplicates. When the example flow is run, it generates a text file to store message IDs and will return "passed" for new messages but "EXCEPTION" for duplicate messages.
Idempotent filter with simple file
Idempotent filter with simple filejaveed_mhd The document discusses how to use an Idempotent Filter in Mule to avoid duplicate messages by checking message IDs. It provides an example of configuring an Idempotent Filter to use a simple-text-file-store to store message IDs in files and check for duplicates. When the example flow is run, it generates a text file to store message IDs and will return "passed" for new messages but throw an exception for duplicate messages.
Mule idempotent filter and Object Store
Mule idempotent filter and Object StoreAnirban Sen Chowdhary Idempotent filters in Mule ensure only unique messages are processed by checking message IDs. They can use different object stores like in-memory, file-based, or managed stores to check for duplicate message IDs. This document demonstrates configuring idempotent filters with simple-text-file-store, in-memory-store, and managed-store object stores. The examples show how idempotent filters can prevent duplicate messages from being processed in a Mule flow.
Filter and object
Filter and objectSon Nguyen Mule provides two types of object stores for persisting data in idempotent filters: in-memory and persistent. The document discusses configuring an idempotent filter with different object store types - simple text file store, in-memory store, and managed store. It provides examples of configuration for each and explains that the filter will store message IDs to prevent duplicate messages. Hitting a sample URL the first time would succeed while a second hit with the same payload would fail due to the idempotent check.
Filter example
Filter exampleManav Prasad The document describes an idempotent filter that ensures only unique messages are received by checking the unique ID of incoming messages. It provides an example message flow configuration using a simple text file store technique to restrict duplicate messages by storing all messages in files and checking for duplicates whenever a new message is received. Testing instructions are included to send the same message twice and show the filter will only allow the first unique message through.
Mulesoft idempotent Message Filter
Mulesoft idempotent Message Filterkumar gaurav This document discusses Mulesoft's Idempotent Message Filter component. It ensures only unique messages pass through a service by checking the unique ID of incoming messages. There are several ways to achieve uniqueness, including using a simple text file store, which is demonstrated in a sample use case of validating unique user requests. The demonstration shows how to configure the Idempotent Message Filter in a flow to restrict duplicate messages from being processed.
Idempotent filter
Idempotent filtercharle819 A brief explanation of Idempotent Filter and how messages are stored to prevent duplication in Mule and a basic example
Using idempotent filter
Using idempotent filterRahul Kumar Overview of Mulesoft's idempotent filter.
This presentation includes sample Snippets, considerations.
Mule esb - How to use Idempotent Filters in 5 minutes
Mule esb - How to use Idempotent Filters in 5 minutesGennaro Spagnoli This document discusses how to use an idempotent filter in Mule ESB to ensure unique messages are received by a service. It explains setting up an HTTP inbound endpoint to trigger a flow, then using an expression filter configured to allow messages to pass only if the expression evaluates to true once, such as a unique name parameter. The document tests sending a message with the same name parameter twice to demonstrate the filter will only allow the first unique message to pass through successfully.
Mule Idempotent Filter - Part I
Mule Idempotent Filter - Part IRAMANAN T D The document discusses Mule's idempotent filter, which ensures that only unique messages are received by a service. It can achieve uniqueness through various object stores and calculates message IDs or hashes messages to identify duplicates. The document also describes attributes and child elements of different idempotent processors like the idempotent filter, idempotent redelivery policy, idempotent receiver router, and idempotent secure hash receiver router.
Mule Idempotent Filter - Part II
Mule Idempotent Filter - Part IIRAMANAN T D This document discusses using a simple text file store with Mule's idempotent message filter to achieve message uniqueness. It presents a use case where a unique URI parameter is used to validate each user request. The flow shows how the idempotent filter checks the text file store for duplicate messages identified by the message payload. Sample XML configuration and testing results are provided, showing the first request succeeding and subsequent duplicate requests failing with an exception.
Mule soft filters_2
Mule soft filters_2abhipokharna This document discusses different types of filters in MuleSoft including message filters, message property filters, idempotent filters, and some more filters like wildcard filters and exception type filters. It provides examples of how each filter can be used and notes that the next session will cover Mule variables and properties, referencing MuleSoft's website for more information.
Filters
FiltersFrancesca Della Corte Filters determine whether a message can proceed through a Mule flow. There are 12 bundled filters that implement basic logic operators or validate message properties, payloads, and schemas. Custom filters can also be created to specify precise conditions a message must meet. Filters return null if conditions are not met, halting processing, but pass the message if conditions are satisfied.
Ad
More from Anirban Sen Chowdhary (20)
Change the game with Game changer
Change the game with Game changerAnirban Sen Chowdhary RingCentral is an award-winning cloud-based communications system with a large developer community called "Game Changer" that connects developers, users, and customers. Through Game Changer, developers can interact, help each other, share ideas, and participate in activities to learn about RingCentral's products and APIs while earning points and rewards. The platform aims to learn and contribute to the community in a fun way.
RingCentral application development overview
RingCentral application development overviewAnirban Sen Chowdhary Ring central application development overview
Overview on ring central errors part 4
Overview on ring central errors part 4Anirban Sen Chowdhary The API allows 10 heavy, 40 medium, 50 light requests per user and 5 authorization requests; exceeding these thresholds will result in a 429 Too Many Requests HTTP error code. The document discusses that when requests begin exceeding limitations, servers commonly return responses with a 429 status.
Setting up your ring central sandbox in steps
Setting up your ring central sandbox in stepsAnirban Sen Chowdhary RingCentral provides a sandbox environment for developers to test and build applications using its APIs. The summary outlines 5 steps to set up a RingCentral sandbox account:
1) Get a developer account on the RingCentral developer portal.
2) Log into the developer account and locate the sandbox account details.
3) Set the password for the sandbox account and log into the online account portal.
4) Create a test application on the developer dashboard by selecting the platform and feature to access via APIs.
5) The application API key and secret can then be used to test the application using the RingCentral APIs.
Overview on ring central errors: part 2
Overview on ring central errors: part 2Anirban Sen Chowdhary This document discusses server errors that can occur in the RingCentral application programming interface (API). Server errors have an HTTP status code in the 50x range and can be difficult to diagnose without access to server logs. Common causes include high traffic or maintenance. If the error persists, the RingCentral developer support team can investigate server logs to resolve the issue.
Overview on ring central errors
Overview on ring central errorsAnirban Sen Chowdhary RingCentral offers communication services like VoIP calling, web meetings, and fax through a secure cloud phone system. Creating RingCentral applications is easy and can be done within minutes by logging into the RingCentral developer account. Once created, applications can access RingCentral APIs based on permissions and features. The RingCentral API uses specific error codes to simplify error processing for client applications. There are different categories of errors like server errors (HTTP 50x), authentication errors (HTTP 40x), and rate limiting errors (HTTP 429).
Call recording overview ring central
Call recording overview ring centralAnirban Sen Chowdhary RingCentral provides call recording capabilities that allow recordings to be retrieved and streamed via their API. This enables uses cases like analyzing recordings to enhance customer interactions. RingCentral's call recording APIs support streaming playback of recordings using HTML5 audio tags without needing to download the file. Automatic call recording is not turned on by default and must be enabled in the account settings.
Ring central engaging with amazon alexa
Ring central engaging with amazon alexaAnirban Sen Chowdhary RingCentral is integrating with Amazon Alexa to allow users to access RingCentral's communication services like voip calling, meetings, and faxes using voice commands with Alexa. This integration allows users to start and control RingCentral meetings, send messages, and make calls just by talking to Alexa. The integration authenticates users with voice recognition and securely connects RingCentral services with Alexa's voice assistant capabilities.
How ring central sdk changing the game
How ring central sdk changing the gameAnirban Sen Chowdhary RingCentral provides communication services like voice calls, SMS, fax, and online meetings through their APIs. They have SDKs available for many programming languages to make it easy for developers to integrate these services into their applications. The RingCentral SDKs handle tasks like authorization and provide helper functions for working with API requests and responses. This allows developers across different platforms and languages to quickly add powerful communication capabilities to their applications.
When ring central connect salesforce
When ring central connect salesforceAnirban Sen Chowdhary RingCentral integrates with Salesforce to provide seamless communication capabilities within the CRM. This improves customer retention, agent productivity, and business processes. The integration empowers the Salesforce system with RingCentral phone features and creates a more collaborative CRM experience. It allows users to create accounts, leads, contacts, and opportunities while on calls through a 360-degree view of customers. The integration is available on all browsers and devices and provides customized reports and dashboards along with accurate call and SMS logs to enhance the CRM experience.
Mule 4 connecting ring central
Mule 4 connecting ring centralAnirban Sen Chowdhary The document describes how to connect RingCentral APIs to send SMS messages using Mulesoft Mule 4. It involves creating a Mule application with a flow containing an HTTP listener, payload transformer, and HTTP request to call the RingCentral send SMS API. The flow first calls the RingCentral authorization API to get an access token, stores it in a variable, and passes it in the header when calling the send SMS API. This allows the application to authenticate and send SMS texts via the RingCentral API using Mule 4.
Ring central sdk
Ring central sdkAnirban Sen Chowdhary RingCentral exposes powerful communication APIs that allow sending messages via SMS, fax, or call from applications integrated with RingCentral. It provides SDKs for languages like Java, PHP, Python, and JavaScript to facilitate API access and handle authentication. The SDKs package RingCentral's API functionality into easy-to-use libraries for each language and handle tasks like token management. This allows developers across platforms and languages to quickly build communication features into their applications.
Ring central with okta
Ring central with oktaAnirban Sen Chowdhary RingCentral and Okta integrate to provide secure single sign-on and identity management for RingCentral users. This allows users to access their RingCentral phone numbers from any mobile device securely. New users created in an organization's Active Directory will be automatically provisioned to RingCentral. The integration provides enterprise single sign-on so users only need to authenticate once to access multiple applications. It improves security, efficiency and simplicity by reducing the need for multiple credentials across different applications.
Ring central connecting salesforce overview
Ring central connecting salesforce overviewAnirban Sen Chowdhary RingCentral is a leading cloud-based communication system that integrates with Salesforce to improve customer retention, agent productivity, and business processes. The integration allows users to create and manage Salesforce records while on calls through RingCentral, providing a 360-degree view of customers. It seamlessly connects the phone system and CRM for improved workflows and increased productivity.
Ring central call logs overview (part 2)
Ring central call logs overview (part 2)Anirban Sen Chowdhary The document discusses RingCentral call logs and APIs. It provides the API URL to access call logs and notes that there is typically a 30 second delay before completed call details are available. It also mentions an API to access active/in-progress calls and that call log and call recording permissions are required. Finally, it notes administrators can enable/disable call log delivery and permissions.
Recently uploaded (20)
Boosting MySQL with Vector Search -THE VECTOR SEARCH CONFERENCE 2025 .pdf
Boosting MySQL with Vector Search -THE VECTOR SEARCH CONFERENCE 2025 .pdfAlkin Tezuysal As the demand for vector databases and Generative AI continues to rise, integrating vector storage and search capabilities into traditional databases has become increasingly important. This session introduces the *MyVector Plugin*, a project that brings native vector storage and similarity search to MySQL. Unlike PostgreSQL, which offers interfaces for adding new data types and index methods, MySQL lacks such extensibility. However, by utilizing MySQL's server component plugin and UDF, the *MyVector Plugin* successfully adds a fully functional vector search feature within the existing MySQL + InnoDB infrastructure, eliminating the need for a separate vector database. The session explains the technical aspects of integrating vector support into MySQL, the challenges posed by its architecture, and real-world use cases that showcase the advantages of combining vector search with MySQL's robust features. Attendees will leave with practical insights on how to add vector search capabilities to their MySQL systems.
TimeSeries Machine Learning - PyData London 2025
TimeSeries Machine Learning - PyData London 2025Suyash Joshi Timeseries Machine Learning - forecasting and anomaly detection with InfluxDB
ELNL2025 - Unlocking the Power of Sensitivity Labels - A Comprehensive Guide....
ELNL2025 - Unlocking the Power of Sensitivity Labels - A Comprehensive Guide....Jasper Oosterveld Sensitivity labels, powered by Microsoft Purview Information Protection, serve as the foundation for classifying and protecting your sensitive data within Microsoft 365. Their importance extends beyond classification and play a crucial role in enforcing governance policies across your Microsoft 365 environment. Join me, a Data Security Consultant and Microsoft MVP, as I share practical tips and tricks to get the full potential of sensitivity labels. I discuss sensitive information types, automatic labeling, and seamless integration with Data Loss Prevention, Teams Premium, and Microsoft 365 Copilot.
AI Agents in Logistics and Supply Chain Applications Benefits and Implementation
AI Agents in Logistics and Supply Chain Applications Benefits and ImplementationChristine Shepherd AI agents are reshaping logistics and supply chain operations by enabling automation, predictive insights, and real-time decision-making across key functions such as demand forecasting, inventory management, procurement, transportation, and warehouse operations. Powered by technologies like machine learning, NLP, computer vision, and robotic process automation, these agents deliver significant benefits including cost reduction, improved efficiency, greater visibility, and enhanced adaptability to market changes. While practical use cases show measurable gains in areas like dynamic routing and real-time inventory tracking, successful implementation requires careful integration with existing systems, quality data, and strategic scaling. Despite challenges such as data integration and change management, AI agents offer a strong competitive edge, with widespread industry adoption expected by 2025.
Improving Developer Productivity With DORA, SPACE, and DevEx
Improving Developer Productivity With DORA, SPACE, and DevExJustin Reock Ready to measure and improve developer productivity in your organization?
Join Justin Reock, Deputy CTO at DX, for an interactive session where you'll learn actionable strategies to measure and increase engineering performance.
Leave this session equipped with a comprehensive understanding of developer productivity and a roadmap to create a high-performing engineering team in your company.
Cybersecurity Fundamentals: Apprentice - Palo Alto Certificate
Cybersecurity Fundamentals: Apprentice - Palo Alto CertificateVICTOR MAESTRE RAMIREZ Cybersecurity Fundamentals: Apprentice - Palo Alto Certificate
Jeremy Millul - A Talented Software Developer
Jeremy Millul - A Talented Software DeveloperJeremy Millul Jeremy Millul is a talented software developer based in NYC, known for leading impactful projects such as a Community Engagement Platform and a Hiking Trail Finder. Using React, MongoDB, and geolocation tools, Jeremy delivers intuitive applications that foster engagement and usability. A graduate of NYU’s Computer Science program, he brings creativity and technical expertise to every project, ensuring seamless user experiences and meaningful results in software development.
Mark Zuckerberg teams up with frenemy Palmer Luckey to shape the future of XR...
Mark Zuckerberg teams up with frenemy Palmer Luckey to shape the future of XR...Scott M. Graffius Mark Zuckerberg teams up with frenemy Palmer Luckey to shape the future of XR/VR/AR wearables 🥽
Drawing on his background in AI, Agile, hardware, software, gaming, and defense, Scott M. Graffius explores the collaboration in “Meta and Anduril’s EagleEye and the Future of XR: How Gaming, AI, and Agile are Transforming Defense.” It’s a powerful case of cross-industry innovation—where gaming meets battlefield tech.
📖 Read the article: https://www.scottgraffius.com/blog/files/meta-and-anduril-eagleeye-and-the-future-of-xr-how-gaming-ai-and-agile-are-transforming-defense.html
#Agile #AI #AR #ArtificialIntelligence #AugmentedReality #Defense #DefenseTech #EagleEye #EmergingTech #ExtendedReality #ExtremeReality #FutureOfTech #GameDev #GameTech #Gaming #GovTech #Hardware #Innovation #Meta #MilitaryInnovation #MixedReality #NationalSecurity #TacticalTech #Tech #TechConvergence #TechInnovation #VirtualReality #XR
Trends Artificial Intelligence - Mary Meeker
Trends Artificial Intelligence - Mary MeekerClive Dickens Mary Meeker’s 2024 AI report highlights a seismic shift in productivity, creativity, and business value driven by generative AI. She charts the rapid adoption of tools like ChatGPT and Midjourney, likening today’s moment to the dawn of the internet. The report emphasizes AI’s impact on knowledge work, software development, and personalized services—while also cautioning about data quality, ethical use, and the human-AI partnership. In short, Meeker sees AI as a transformative force accelerating innovation and redefining how we live and work.
The case for on-premises AI
The case for on-premises AIPrincipled Technologies Exploring the advantages of on-premises Dell PowerEdge servers with AMD EPYC processors vs. the cloud for small to medium businesses’ AI workloads
AI initiatives can bring tremendous value to your business, but you need to support your new AI workloads effectively. That means choosing the best possible infrastructure for your needs—and many companies are finding that the cloud isn’t right for them. According to a recent Rackspace survey of IT executives, 69 percent of companies have moved some of their applications on-premises from the cloud, with half of those citing security and compliance as the reason and 44 percent citing cost.
On-premises solutions provide a number of advantages. With full control over your security infrastructure, you can be certain that all compliance requirements remain firmly in the hands of your IT team. Opting for on-premises also gives you the ability to design your infrastructure to the precise needs of that team and your new AI workloads. Depending on the workload, you may also see performance benefits, along with more predictable costs. As you start to build your next AI initiative, consider an on-premises solution utilizing AMD EPYC processor-powered Dell PowerEdge servers.
LSNIF: Locally-Subdivided Neural Intersection Function
LSNIF: Locally-Subdivided Neural Intersection FunctionTakahiro Harada Neural representations have shown the potential to accelerate ray casting in a conventional ray-tracing-based rendering pipeline. We introduce a novel approach called Locally-Subdivided Neural Intersection Function (LSNIF) that replaces bottom-level BVHs used as traditional geometric representations with a neural network. Our method introduces a sparse hash grid encoding scheme incorporating geometry voxelization, a scene-agnostic training data collection, and a tailored loss function. It enables the network to output not only visibility but also hit-point information and material indices. LSNIF can be trained offline for a single object, allowing us to use LSNIF as a replacement for its corresponding BVH. With these designs, the network can handle hit-point queries from any arbitrary viewpoint, supporting all types of rays in the rendering pipeline. We demonstrate that LSNIF can render a variety of scenes, including real-world scenes designed for other path tracers, while achieving a memory footprint reduction of up to 106.2x compared to a compressed BVH.
https://arxiv.org/abs/2504.21627
IntroSlides-May-BuildWithAi-EarthEngine.pdf
IntroSlides-May-BuildWithAi-EarthEngine.pdfLuiz Carneiro Introduction slides for the #BuildWithAi workshop on the 27th of May 2025 at the Google Office in Munich.
If You Use Databricks, You Definitely Need FME
If You Use Databricks, You Definitely Need FMESafe Software DataBricks makes it easy to use Apache Spark. It provides a platform with the potential to analyze and process huge volumes of data. Sounds awesome. The sales brochure reads as if it is a can-do-all data integration platform. Does it replace our beloved FME platform or does it provide opportunities for FME to shine? Challenge accepted
End-to-end Assurance for SD-WAN & SASE with ThousandEyes
End-to-end Assurance for SD-WAN & SASE with ThousandEyesThousandEyes End-to-end Assurance for SD-WAN & SASE with ThousandEyes
Data Virtualization: Bringing the Power of FME to Any Application
Data Virtualization: Bringing the Power of FME to Any ApplicationSafe Software Imagine building web applications or dashboards on top of all your systems. With FME’s new Data Virtualization feature, you can deliver the full CRUD (create, read, update, and delete) capabilities on top of all your data that exploit the full power of FME’s all data, any AI capabilities. Data Virtualization enables you to build OpenAPI compliant API endpoints using FME Form’s no-code development platform.
In this webinar, you’ll see how easy it is to turn complex data into real-time, usable REST API based services. We’ll walk through a real example of building a map-based app using FME’s Data Virtualization, and show you how to get started in your own environment – no dev team required.
What you’ll take away:
-How to build live applications and dashboards with federated data
-Ways to control what’s exposed: filter, transform, and secure responses
-How to scale access with caching, asynchronous web call support, with API endpoint level security.
-Where this fits in your stack: from web apps, to AI, to automation
Whether you’re building internal tools, public portals, or powering automation – this webinar is your starting point to real-time data delivery.
Your startup on AWS - How to architect and maintain a Lean and Mean account
Your startup on AWS - How to architect and maintain a Lean and Mean accountangelo60207 Prevent infrastructure costs from becoming a significant line item on your startup’s budget! Serial entrepreneur and software architect Angelo Mandato will share his experience with AWS Activate (startup credits from AWS) and knowledge on how to architect a lean and mean AWS account ideal for budget minded and bootstrapped startups. In this session you will learn how to manage a production ready AWS account capable of scaling as your startup grows for less than $100/month before credits. We will discuss AWS Budgets, Cost Explorer, architect priorities, and the importance of having flexible, optimized Infrastructure as Code. We will wrap everything up discussing opportunities where to save with AWS services such as S3, EC2, Load Balancers, Lambda Functions, RDS, and many others.
Your startup on AWS - How to architect and maintain a Lean and Mean account J...
Your startup on AWS - How to architect and maintain a Lean and Mean account J...angelo60207 Prevent infrastructure costs from becoming a significant line item on your startup’s budget! Serial entrepreneur and software architect Angelo Mandato will share his experience with AWS Activate (startup credits from AWS) and knowledge on how to architect a lean and mean AWS account ideal for budget minded and bootstrapped startups. In this session you will learn how to manage a production ready AWS account capable of scaling as your startup grows for less than $100/month before credits. We will discuss AWS Budgets, Cost Explorer, architect priorities, and the importance of having flexible, optimized Infrastructure as Code. We will wrap everything up discussing opportunities where to save with AWS services such as S3, EC2, Load Balancers, Lambda Functions, RDS, and many others.
Evaluation Challenges in Using Generative AI for Science & Technical Content
Evaluation Challenges in Using Generative AI for Science & Technical ContentPaul Groth Evaluation Challenges in Using Generative AI for Science & Technical Content.
Foundation Models show impressive results in a wide-range of tasks on scientific and legal content from information extraction to question answering and even literature synthesis. However, standard evaluation approaches (e.g. comparing to ground truth) often don't seem to work. Qualitatively the results look great but quantitive scores do not align with these observations. In this talk, I discuss the challenges we've face in our lab in evaluation. I then outline potential routes forward.
Idempotent filter with simple file
- 1. By Anirban Sen Chowdhary
- 2. Idempotent Filter is an important message filter in Mule platform which ensures that only unique messages are received by a service by checking the unique ID of the incoming message. We use Idempotent Filter to avoid any duplicate message in our Mule flow We will be demonstrating a simple example of Idempotent Filter using simple- text-file-store.
- 3. Idempotent Filter with simple-text-file-store :- We can configure it following way :- Here you can see that we have configured our Idempotent Filter with simple-text- file-store. So, now this filter will restrict any duplicates message it finds. simple-text-file-store technique will store all the messages in file and will check the file to detect duplicates whenever it receive a input message. For each message the files will be generated.
- 4. You will see that we will run our Mule application it will generate text file in our Mule application where it will store all the message with ID to avoid the duplicate :-
- 5. Now, we can configure with any of the options shown here, we will get following Mule flow :-
- 6. Our Mule Config will be :-
- 7. So, we will test our application by hitting the following url http://localhost:8081/path/test for the first time we will get :- For the first time we will see browser display “passed” as the message payload is new and unique (path/test is the message payload here)
- 8. And then if we hit the same url http://localhost:8081/path/test again, will get the following :- For the second time we will see browser display “EXCEPTION” as the message payload is now same and duplicate (path/test is the message payload here)
- 9. Hope I am able to make it clear on how to implement Idempotent Filter with different ways and you can now try by your own and experiment with this powerful filter of Mule. Hope you enjoyed this simpler version