SlideShare a Scribd company logo
Mule Batch
Processing
Batch Processing
Batch component is used to process huge messages in batches. In batch we have 3
phases.
1. Input
2. Process Records
3. On complete
Input:
Input phase is used to prepare a collection object with input message.
Because process records phase expects a collection object.
Process Records:
Process Record phase expects a collection object to process the each
record of collection in individually and parallel. Here each object of collection is a
record.
On Complete:
On complete phase is used to summarize the flow. Following variables are
available in On Complete phase to get the status of flow.
• Count of Successful records
• Count of Failure records
• Count of total records.
Example:
In the following example, it explains how to transform CSV to XML using batch.
This example exposes a HTTP rest service.
In the main flow input csv file path sets to payload and refer to a batch job.
In Input phase, an expression component is used to read file
(src/main/resources/input.csv) data. This expression component refers to a file
(src/main/resources/ReadFile.txt) which has code to read file data. Another
expression component has below expression to create a collection object.
payload = new com.techm.common.util.LineIterator(payload);
LineIterator is our custom class which implements Iterator Interface to implement
collection object. Below is code of LineIterator class.
Note : Java Code Continuation from line 31 on next slide.
In Process Records phase, we have two batch steps to transform payload from
csv to xml using datamapper and write the xml data into a file. Second batch
step contains batch commit. The message processors which are in batch
commit scope get execute depends of size of batch commit.
<batch:commit size="5" doc:name="Batch Commit">
This batch commit get executed for every 5 records as configured.
On Complete phase has one logger component which logs successful, failure
and total no of records.
Note : SOAP UI project to test this application is placed in src/test/resources.
Thank You All

More Related Content

What's hot

Flink Forward SF 2017: Stephan Ewen - Experiences running Flink at Very Large...
Flink Forward SF 2017: Stephan Ewen - Experiences running Flink at Very Large...Flink Forward SF 2017: Stephan Ewen - Experiences running Flink at Very Large...
Flink Forward SF 2017: Stephan Ewen - Experiences running Flink at Very Large...
Flink Forward
 
Flink Forward Berlin 2017: Maciek Próchniak - TouK Nussknacker - creating Fli...
Flink Forward Berlin 2017: Maciek Próchniak - TouK Nussknacker - creating Fli...Flink Forward Berlin 2017: Maciek Próchniak - TouK Nussknacker - creating Fli...
Flink Forward Berlin 2017: Maciek Próchniak - TouK Nussknacker - creating Fli...
Flink Forward
 
Flink Forward SF 2017: Stefan Richter - Improvements for large state and reco...
Flink Forward SF 2017: Stefan Richter - Improvements for large state and reco...Flink Forward SF 2017: Stefan Richter - Improvements for large state and reco...
Flink Forward SF 2017: Stefan Richter - Improvements for large state and reco...
Flink Forward
 
Flink Forward Berlin 2017: Francesco Versaci - Integrating Flink and Kafka in...
Flink Forward Berlin 2017: Francesco Versaci - Integrating Flink and Kafka in...Flink Forward Berlin 2017: Francesco Versaci - Integrating Flink and Kafka in...
Flink Forward Berlin 2017: Francesco Versaci - Integrating Flink and Kafka in...
Flink Forward
 
Flink Forward Berlin 2017: Boris Lublinsky, Stavros Kontopoulos - Introducing...
Flink Forward Berlin 2017: Boris Lublinsky, Stavros Kontopoulos - Introducing...Flink Forward Berlin 2017: Boris Lublinsky, Stavros Kontopoulos - Introducing...
Flink Forward Berlin 2017: Boris Lublinsky, Stavros Kontopoulos - Introducing...
Flink Forward
 
Continuous Processing with Apache Flink - Strata London 2016
Continuous Processing with Apache Flink - Strata London 2016Continuous Processing with Apache Flink - Strata London 2016
Continuous Processing with Apache Flink - Strata London 2016
Stephan Ewen
 
Stream Loops on Flink - Reinventing the wheel for the streaming era
Stream Loops on Flink - Reinventing the wheel for the streaming eraStream Loops on Flink - Reinventing the wheel for the streaming era
Stream Loops on Flink - Reinventing the wheel for the streaming era
Paris Carbone
 
Flink Forward Berlin 2017: Zohar Mizrahi - Python Streaming API
Flink Forward Berlin 2017: Zohar Mizrahi - Python Streaming APIFlink Forward Berlin 2017: Zohar Mizrahi - Python Streaming API
Flink Forward Berlin 2017: Zohar Mizrahi - Python Streaming API
Flink Forward
 
Apache flink 1.0.0 overview
Apache flink 1.0.0 overviewApache flink 1.0.0 overview
Apache flink 1.0.0 overview
MapR Technologies
 
MicroCPH: Observability and Product Release
MicroCPH: Observability and Product ReleaseMicroCPH: Observability and Product Release
MicroCPH: Observability and Product Release
Sneha Inguva
 
Flink Forward SF 2017: Stephan Ewen - Convergence of real-time analytics and ...
Flink Forward SF 2017: Stephan Ewen - Convergence of real-time analytics and ...Flink Forward SF 2017: Stephan Ewen - Convergence of real-time analytics and ...
Flink Forward SF 2017: Stephan Ewen - Convergence of real-time analytics and ...
Flink Forward
 
Flink Connector Development Tips & Tricks
Flink Connector Development Tips & TricksFlink Connector Development Tips & Tricks
Flink Connector Development Tips & Tricks
Eron Wright
 
Flink Forward SF 2017: Timo Walther - Table & SQL API – unified APIs for bat...
Flink Forward SF 2017: Timo Walther -  Table & SQL API – unified APIs for bat...Flink Forward SF 2017: Timo Walther -  Table & SQL API – unified APIs for bat...
Flink Forward SF 2017: Timo Walther - Table & SQL API – unified APIs for bat...
Flink Forward
 
I²: Interactive Real-Time Visualization for Streaming Data with Apache Flink ...
I²: Interactive Real-Time Visualization for Streaming Data with Apache Flink ...I²: Interactive Real-Time Visualization for Streaming Data with Apache Flink ...
I²: Interactive Real-Time Visualization for Streaming Data with Apache Flink ...
Jonas Traub
 
Flink Forward Berlin 2018: Shriya Arora - "Taming large-state to join dataset...
Flink Forward Berlin 2018: Shriya Arora - "Taming large-state to join dataset...Flink Forward Berlin 2018: Shriya Arora - "Taming large-state to join dataset...
Flink Forward Berlin 2018: Shriya Arora - "Taming large-state to join dataset...
Flink Forward
 
Flink Forward SF 2017: Till Rohrmann - Redesigning Apache Flink’s Distributed...
Flink Forward SF 2017: Till Rohrmann - Redesigning Apache Flink’s Distributed...Flink Forward SF 2017: Till Rohrmann - Redesigning Apache Flink’s Distributed...
Flink Forward SF 2017: Till Rohrmann - Redesigning Apache Flink’s Distributed...
Flink Forward
 
Java spring batch
Java spring batchJava spring batch
Flink Forward Berlin 2017: Andreas Kunft - Efficiently executing R Dataframes...
Flink Forward Berlin 2017: Andreas Kunft - Efficiently executing R Dataframes...Flink Forward Berlin 2017: Andreas Kunft - Efficiently executing R Dataframes...
Flink Forward Berlin 2017: Andreas Kunft - Efficiently executing R Dataframes...
Flink Forward
 
What's new in 1.9.0 blink planner - Kurt Young, Alibaba
What's new in 1.9.0 blink planner - Kurt Young, AlibabaWhat's new in 1.9.0 blink planner - Kurt Young, Alibaba
What's new in 1.9.0 blink planner - Kurt Young, Alibaba
Flink Forward
 
Event driven-arch
Event driven-archEvent driven-arch
Event driven-arch
Mohammed Shoaib
 

What's hot (20)

Flink Forward SF 2017: Stephan Ewen - Experiences running Flink at Very Large...
Flink Forward SF 2017: Stephan Ewen - Experiences running Flink at Very Large...Flink Forward SF 2017: Stephan Ewen - Experiences running Flink at Very Large...
Flink Forward SF 2017: Stephan Ewen - Experiences running Flink at Very Large...
 
Flink Forward Berlin 2017: Maciek Próchniak - TouK Nussknacker - creating Fli...
Flink Forward Berlin 2017: Maciek Próchniak - TouK Nussknacker - creating Fli...Flink Forward Berlin 2017: Maciek Próchniak - TouK Nussknacker - creating Fli...
Flink Forward Berlin 2017: Maciek Próchniak - TouK Nussknacker - creating Fli...
 
Flink Forward SF 2017: Stefan Richter - Improvements for large state and reco...
Flink Forward SF 2017: Stefan Richter - Improvements for large state and reco...Flink Forward SF 2017: Stefan Richter - Improvements for large state and reco...
Flink Forward SF 2017: Stefan Richter - Improvements for large state and reco...
 
Flink Forward Berlin 2017: Francesco Versaci - Integrating Flink and Kafka in...
Flink Forward Berlin 2017: Francesco Versaci - Integrating Flink and Kafka in...Flink Forward Berlin 2017: Francesco Versaci - Integrating Flink and Kafka in...
Flink Forward Berlin 2017: Francesco Versaci - Integrating Flink and Kafka in...
 
Flink Forward Berlin 2017: Boris Lublinsky, Stavros Kontopoulos - Introducing...
Flink Forward Berlin 2017: Boris Lublinsky, Stavros Kontopoulos - Introducing...Flink Forward Berlin 2017: Boris Lublinsky, Stavros Kontopoulos - Introducing...
Flink Forward Berlin 2017: Boris Lublinsky, Stavros Kontopoulos - Introducing...
 
Continuous Processing with Apache Flink - Strata London 2016
Continuous Processing with Apache Flink - Strata London 2016Continuous Processing with Apache Flink - Strata London 2016
Continuous Processing with Apache Flink - Strata London 2016
 
Stream Loops on Flink - Reinventing the wheel for the streaming era
Stream Loops on Flink - Reinventing the wheel for the streaming eraStream Loops on Flink - Reinventing the wheel for the streaming era
Stream Loops on Flink - Reinventing the wheel for the streaming era
 
Flink Forward Berlin 2017: Zohar Mizrahi - Python Streaming API
Flink Forward Berlin 2017: Zohar Mizrahi - Python Streaming APIFlink Forward Berlin 2017: Zohar Mizrahi - Python Streaming API
Flink Forward Berlin 2017: Zohar Mizrahi - Python Streaming API
 
Apache flink 1.0.0 overview
Apache flink 1.0.0 overviewApache flink 1.0.0 overview
Apache flink 1.0.0 overview
 
MicroCPH: Observability and Product Release
MicroCPH: Observability and Product ReleaseMicroCPH: Observability and Product Release
MicroCPH: Observability and Product Release
 
Flink Forward SF 2017: Stephan Ewen - Convergence of real-time analytics and ...
Flink Forward SF 2017: Stephan Ewen - Convergence of real-time analytics and ...Flink Forward SF 2017: Stephan Ewen - Convergence of real-time analytics and ...
Flink Forward SF 2017: Stephan Ewen - Convergence of real-time analytics and ...
 
Flink Connector Development Tips & Tricks
Flink Connector Development Tips & TricksFlink Connector Development Tips & Tricks
Flink Connector Development Tips & Tricks
 
Flink Forward SF 2017: Timo Walther - Table & SQL API – unified APIs for bat...
Flink Forward SF 2017: Timo Walther -  Table & SQL API – unified APIs for bat...Flink Forward SF 2017: Timo Walther -  Table & SQL API – unified APIs for bat...
Flink Forward SF 2017: Timo Walther - Table & SQL API – unified APIs for bat...
 
I²: Interactive Real-Time Visualization for Streaming Data with Apache Flink ...
I²: Interactive Real-Time Visualization for Streaming Data with Apache Flink ...I²: Interactive Real-Time Visualization for Streaming Data with Apache Flink ...
I²: Interactive Real-Time Visualization for Streaming Data with Apache Flink ...
 
Flink Forward Berlin 2018: Shriya Arora - "Taming large-state to join dataset...
Flink Forward Berlin 2018: Shriya Arora - "Taming large-state to join dataset...Flink Forward Berlin 2018: Shriya Arora - "Taming large-state to join dataset...
Flink Forward Berlin 2018: Shriya Arora - "Taming large-state to join dataset...
 
Flink Forward SF 2017: Till Rohrmann - Redesigning Apache Flink’s Distributed...
Flink Forward SF 2017: Till Rohrmann - Redesigning Apache Flink’s Distributed...Flink Forward SF 2017: Till Rohrmann - Redesigning Apache Flink’s Distributed...
Flink Forward SF 2017: Till Rohrmann - Redesigning Apache Flink’s Distributed...
 
Java spring batch
Java spring batchJava spring batch
Java spring batch
 
Flink Forward Berlin 2017: Andreas Kunft - Efficiently executing R Dataframes...
Flink Forward Berlin 2017: Andreas Kunft - Efficiently executing R Dataframes...Flink Forward Berlin 2017: Andreas Kunft - Efficiently executing R Dataframes...
Flink Forward Berlin 2017: Andreas Kunft - Efficiently executing R Dataframes...
 
What's new in 1.9.0 blink planner - Kurt Young, Alibaba
What's new in 1.9.0 blink planner - Kurt Young, AlibabaWhat's new in 1.9.0 blink planner - Kurt Young, Alibaba
What's new in 1.9.0 blink planner - Kurt Young, Alibaba
 
Event driven-arch
Event driven-archEvent driven-arch
Event driven-arch
 

Viewers also liked

Presentacion A lus do mundo. Santiago 2016. Alumnado
Presentacion A lus do mundo. Santiago 2016. AlumnadoPresentacion A lus do mundo. Santiago 2016. Alumnado
Presentacion A lus do mundo. Santiago 2016. Alumnado
IES Poeta Díaz Castro
 
Word 2 tha mutha.pt.249
Word 2 tha mutha.pt.249Word 2 tha mutha.pt.249
Word 2 tha mutha.pt.249
Celifahmain
 
Cie 10 odontologia
Cie 10 odontologiaCie 10 odontologia
Cie 10 odontologia
Guille aguero Ricra
 
STARMALL BATAAN
STARMALL BATAANSTARMALL BATAAN
STARMALL BATAAN
Paola Marie Caluya,rMP
 
Dimitar (Mitko) Frangov - Selection de travaux en assistant photographe
Dimitar (Mitko) Frangov - Selection de travaux en assistant photographeDimitar (Mitko) Frangov - Selection de travaux en assistant photographe
Dimitar (Mitko) Frangov - Selection de travaux en assistant photographeDimitar Frangov
 
Energias Alternativas
Energias AlternativasEnergias Alternativas
Energias Alternativas
Facundo Campo
 
Resulset
ResulsetResulset
Variables aleatorias y distribuciones de probabilidad
Variables aleatorias y distribuciones de probabilidadVariables aleatorias y distribuciones de probabilidad
Variables aleatorias y distribuciones de probabilidad
Laura Pacheco lobo
 
GST COUNCIL
GST COUNCILGST COUNCIL
GST COUNCIL
anshuman a s
 
The climateof india
The climateof indiaThe climateof india
The climateof india
eng2group3work
 
Trouble-free travel (final)
Trouble-free travel (final)Trouble-free travel (final)
Trouble-free travel (final)
eng2group3work
 
Word 2 tha mutha.pt.263
Word 2 tha mutha.pt.263Word 2 tha mutha.pt.263
Word 2 tha mutha.pt.263
Celifahmain
 
J table
J tableJ table
Climate change
Climate changeClimate change
Climate change
eng2group3work
 
Niños con nee
Niños con neeNiños con nee
JAVA
JAVAJAVA
Chungresume2016-17
Chungresume2016-17Chungresume2016-17
Chungresume2016-17
Eric Chung
 

Viewers also liked (18)

Presentacion A lus do mundo. Santiago 2016. Alumnado
Presentacion A lus do mundo. Santiago 2016. AlumnadoPresentacion A lus do mundo. Santiago 2016. Alumnado
Presentacion A lus do mundo. Santiago 2016. Alumnado
 
Word 2 tha mutha.pt.249
Word 2 tha mutha.pt.249Word 2 tha mutha.pt.249
Word 2 tha mutha.pt.249
 
Cie 10 odontologia
Cie 10 odontologiaCie 10 odontologia
Cie 10 odontologia
 
STARMALL BATAAN
STARMALL BATAANSTARMALL BATAAN
STARMALL BATAAN
 
Dimitar (Mitko) Frangov - Selection de travaux en assistant photographe
Dimitar (Mitko) Frangov - Selection de travaux en assistant photographeDimitar (Mitko) Frangov - Selection de travaux en assistant photographe
Dimitar (Mitko) Frangov - Selection de travaux en assistant photographe
 
Energias Alternativas
Energias AlternativasEnergias Alternativas
Energias Alternativas
 
عرض_الجمعية[1]
عرض_الجمعية[1]عرض_الجمعية[1]
عرض_الجمعية[1]
 
Resulset
ResulsetResulset
Resulset
 
Variables aleatorias y distribuciones de probabilidad
Variables aleatorias y distribuciones de probabilidadVariables aleatorias y distribuciones de probabilidad
Variables aleatorias y distribuciones de probabilidad
 
GST COUNCIL
GST COUNCILGST COUNCIL
GST COUNCIL
 
The climateof india
The climateof indiaThe climateof india
The climateof india
 
Trouble-free travel (final)
Trouble-free travel (final)Trouble-free travel (final)
Trouble-free travel (final)
 
Word 2 tha mutha.pt.263
Word 2 tha mutha.pt.263Word 2 tha mutha.pt.263
Word 2 tha mutha.pt.263
 
J table
J tableJ table
J table
 
Climate change
Climate changeClimate change
Climate change
 
Niños con nee
Niños con neeNiños con nee
Niños con nee
 
JAVA
JAVAJAVA
JAVA
 
Chungresume2016-17
Chungresume2016-17Chungresume2016-17
Chungresume2016-17
 

Similar to Mulebatch

Mule batch processing
Mule batch processingMule batch processing
Mule batch processing
Ravinder Singh
 
Mule batch
Mule batchMule batch
Mule batch
Gandham38
 
Batch processing
Batch processingBatch processing
Batch processing
Harish43
 
Batch processing
Batch processingBatch processing
Batch processing
Harish43
 
Batch processing
Batch processingBatch processing
Batch processing
bapiraju
 
Introduction to transaction processing concepts and theory
Introduction to transaction processing concepts and theoryIntroduction to transaction processing concepts and theory
Introduction to transaction processing concepts and theory
Zainab Almugbel
 
What is COTI?
What is COTI? What is COTI?
What is COTI?
Ovidius GmbH
 
Matopt
MatoptMatopt
My ppt hpc u4
My ppt hpc u4My ppt hpc u4
Toby3
Toby3Toby3
Toby3
TinouTest
 
xxxx
xxxxxxxx
xxxx
TinouTest
 
yyyyxxxdd
yyyyxxxddyyyyxxxdd
yyyyxxxdd
TinouTest
 
new title
new titlenew title
new title
TinouTest
 
yyyyxxx
yyyyxxxyyyyxxx
yyyyxxx
TinouTest
 
Toby2
Toby2Toby2
Toby2
TinouTest
 
Tinoub1
Tinoub1Tinoub1
Tinoub1
TinouTest
 
yyyyxxxdd
yyyyxxxddyyyyxxxdd
yyyyxxxdd
TinouTest
 
Tinoub1
Tinoub1Tinoub1
Tinoub1
TinouTest
 
Monit
MonitMonit
Toby6
Toby6Toby6
Toby6
TinouTest
 

Similar to Mulebatch (20)

Mule batch processing
Mule batch processingMule batch processing
Mule batch processing
 
Mule batch
Mule batchMule batch
Mule batch
 
Batch processing
Batch processingBatch processing
Batch processing
 
Batch processing
Batch processingBatch processing
Batch processing
 
Batch processing
Batch processingBatch processing
Batch processing
 
Introduction to transaction processing concepts and theory
Introduction to transaction processing concepts and theoryIntroduction to transaction processing concepts and theory
Introduction to transaction processing concepts and theory
 
What is COTI?
What is COTI? What is COTI?
What is COTI?
 
Matopt
MatoptMatopt
Matopt
 
My ppt hpc u4
My ppt hpc u4My ppt hpc u4
My ppt hpc u4
 
Toby3
Toby3Toby3
Toby3
 
xxxx
xxxxxxxx
xxxx
 
yyyyxxxdd
yyyyxxxddyyyyxxxdd
yyyyxxxdd
 
new title
new titlenew title
new title
 
yyyyxxx
yyyyxxxyyyyxxx
yyyyxxx
 
Toby2
Toby2Toby2
Toby2
 
Tinoub1
Tinoub1Tinoub1
Tinoub1
 
yyyyxxxdd
yyyyxxxddyyyyxxxdd
yyyyxxxdd
 
Tinoub1
Tinoub1Tinoub1
Tinoub1
 
Monit
MonitMonit
Monit
 
Toby6
Toby6Toby6
Toby6
 

Recently uploaded

Data Driven Maintenance | UReason Webinar
Data Driven Maintenance | UReason WebinarData Driven Maintenance | UReason Webinar
Data Driven Maintenance | UReason Webinar
UReason
 
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student MemberIEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
VICTOR MAESTRE RAMIREZ
 
Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...
IJECEIAES
 
Curve Fitting in Numerical Methods Regression
Curve Fitting in Numerical Methods RegressionCurve Fitting in Numerical Methods Regression
Curve Fitting in Numerical Methods Regression
Nada Hikmah
 
Properties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptxProperties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptx
MDSABBIROJJAMANPAYEL
 
一比一原版(爱大毕业证书)爱荷华大学毕业证如何办理
一比一原版(爱大毕业证书)爱荷华大学毕业证如何办理一比一原版(爱大毕业证书)爱荷华大学毕业证如何办理
一比一原版(爱大毕业证书)爱荷华大学毕业证如何办理
nedcocy
 
Rainfall intensity duration frequency curve statistical analysis and modeling...
Rainfall intensity duration frequency curve statistical analysis and modeling...Rainfall intensity duration frequency curve statistical analysis and modeling...
Rainfall intensity duration frequency curve statistical analysis and modeling...
bijceesjournal
 
22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt
KrishnaveniKrishnara1
 
4. Mosca vol I -Fisica-Tipler-5ta-Edicion-Vol-1.pdf
4. Mosca vol I -Fisica-Tipler-5ta-Edicion-Vol-1.pdf4. Mosca vol I -Fisica-Tipler-5ta-Edicion-Vol-1.pdf
4. Mosca vol I -Fisica-Tipler-5ta-Edicion-Vol-1.pdf
Gino153088
 
132/33KV substation case study Presentation
132/33KV substation case study Presentation132/33KV substation case study Presentation
132/33KV substation case study Presentation
kandramariana6
 
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
ecqow
 
Software Engineering and Project Management - Introduction, Modeling Concepts...
Software Engineering and Project Management - Introduction, Modeling Concepts...Software Engineering and Project Management - Introduction, Modeling Concepts...
Software Engineering and Project Management - Introduction, Modeling Concepts...
Prakhyath Rai
 
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELDEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
ijaia
 
Digital Twins Computer Networking Paper Presentation.pptx
Digital Twins Computer Networking Paper Presentation.pptxDigital Twins Computer Networking Paper Presentation.pptx
Digital Twins Computer Networking Paper Presentation.pptx
aryanpankaj78
 
Null Bangalore | Pentesters Approach to AWS IAM
Null Bangalore | Pentesters Approach to AWS IAMNull Bangalore | Pentesters Approach to AWS IAM
Null Bangalore | Pentesters Approach to AWS IAM
Divyanshu
 
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
Yasser Mahgoub
 
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoringEmbedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
IJECEIAES
 
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...
PriyankaKilaniya
 
Welding Metallurgy Ferrous Materials.pdf
Welding Metallurgy Ferrous Materials.pdfWelding Metallurgy Ferrous Materials.pdf
Welding Metallurgy Ferrous Materials.pdf
AjmalKhan50578
 
Design and optimization of ion propulsion drone
Design and optimization of ion propulsion droneDesign and optimization of ion propulsion drone
Design and optimization of ion propulsion drone
bjmsejournal
 

Recently uploaded (20)

Data Driven Maintenance | UReason Webinar
Data Driven Maintenance | UReason WebinarData Driven Maintenance | UReason Webinar
Data Driven Maintenance | UReason Webinar
 
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student MemberIEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
 
Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...
 
Curve Fitting in Numerical Methods Regression
Curve Fitting in Numerical Methods RegressionCurve Fitting in Numerical Methods Regression
Curve Fitting in Numerical Methods Regression
 
Properties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptxProperties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptx
 
一比一原版(爱大毕业证书)爱荷华大学毕业证如何办理
一比一原版(爱大毕业证书)爱荷华大学毕业证如何办理一比一原版(爱大毕业证书)爱荷华大学毕业证如何办理
一比一原版(爱大毕业证书)爱荷华大学毕业证如何办理
 
Rainfall intensity duration frequency curve statistical analysis and modeling...
Rainfall intensity duration frequency curve statistical analysis and modeling...Rainfall intensity duration frequency curve statistical analysis and modeling...
Rainfall intensity duration frequency curve statistical analysis and modeling...
 
22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt
 
4. Mosca vol I -Fisica-Tipler-5ta-Edicion-Vol-1.pdf
4. Mosca vol I -Fisica-Tipler-5ta-Edicion-Vol-1.pdf4. Mosca vol I -Fisica-Tipler-5ta-Edicion-Vol-1.pdf
4. Mosca vol I -Fisica-Tipler-5ta-Edicion-Vol-1.pdf
 
132/33KV substation case study Presentation
132/33KV substation case study Presentation132/33KV substation case study Presentation
132/33KV substation case study Presentation
 
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
 
Software Engineering and Project Management - Introduction, Modeling Concepts...
Software Engineering and Project Management - Introduction, Modeling Concepts...Software Engineering and Project Management - Introduction, Modeling Concepts...
Software Engineering and Project Management - Introduction, Modeling Concepts...
 
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELDEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
 
Digital Twins Computer Networking Paper Presentation.pptx
Digital Twins Computer Networking Paper Presentation.pptxDigital Twins Computer Networking Paper Presentation.pptx
Digital Twins Computer Networking Paper Presentation.pptx
 
Null Bangalore | Pentesters Approach to AWS IAM
Null Bangalore | Pentesters Approach to AWS IAMNull Bangalore | Pentesters Approach to AWS IAM
Null Bangalore | Pentesters Approach to AWS IAM
 
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
 
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoringEmbedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
 
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...
 
Welding Metallurgy Ferrous Materials.pdf
Welding Metallurgy Ferrous Materials.pdfWelding Metallurgy Ferrous Materials.pdf
Welding Metallurgy Ferrous Materials.pdf
 
Design and optimization of ion propulsion drone
Design and optimization of ion propulsion droneDesign and optimization of ion propulsion drone
Design and optimization of ion propulsion drone
 

Mulebatch

  • 2. Batch Processing Batch component is used to process huge messages in batches. In batch we have 3 phases. 1. Input 2. Process Records 3. On complete Input: Input phase is used to prepare a collection object with input message. Because process records phase expects a collection object.
  • 3. Process Records: Process Record phase expects a collection object to process the each record of collection in individually and parallel. Here each object of collection is a record. On Complete: On complete phase is used to summarize the flow. Following variables are available in On Complete phase to get the status of flow. • Count of Successful records • Count of Failure records • Count of total records.
  • 4. Example: In the following example, it explains how to transform CSV to XML using batch. This example exposes a HTTP rest service.
  • 5. In the main flow input csv file path sets to payload and refer to a batch job.
  • 6. In Input phase, an expression component is used to read file (src/main/resources/input.csv) data. This expression component refers to a file (src/main/resources/ReadFile.txt) which has code to read file data. Another expression component has below expression to create a collection object. payload = new com.techm.common.util.LineIterator(payload); LineIterator is our custom class which implements Iterator Interface to implement collection object. Below is code of LineIterator class.
  • 7. Note : Java Code Continuation from line 31 on next slide.
  • 8.
  • 9. In Process Records phase, we have two batch steps to transform payload from csv to xml using datamapper and write the xml data into a file. Second batch step contains batch commit. The message processors which are in batch commit scope get execute depends of size of batch commit. <batch:commit size="5" doc:name="Batch Commit"> This batch commit get executed for every 5 records as configured. On Complete phase has one logger component which logs successful, failure and total no of records. Note : SOAP UI project to test this application is placed in src/test/resources.