tExtractJSONFields

Extracts the desired data from JSON fields based on the JSONPath or XPath
query.

Depending on the Talend solution you
are using, this component can be used in one, some or all of the following Job
frameworks:

Standard: see tExtractJSONFields Standard properties.

The component in this framework is generally available.
MapReduce: see tExtractJSONFields MapReduce properties.

The component in this framework is available only if you have subscribed to one
of the
Talend
solutions with Big Data.
Spark Batch:
see tExtractJSONFields properties for Apache Spark Batch.

The component in this framework is available only if you have subscribed to one
of the
Talend
solutions with Big Data.
Spark Streaming:
see tExtractJSONFields properties for Apache Spark Streaming.

The component in this framework is available only if you have subscribed to Talend Real-time Big Data Platform or Talend Data
Fabric.
Storm: see tExtractJSONFields Storm properties.

The component in this framework is available only if you have subscribed to Talend Real-time Big Data Platform or Talend Data
Fabric.

tExtractJSONFields Standard properties

These properties are used to configure tExtractJSONFields running in the Standard Job framework.

The Standard
tExtractJSONFields component belongs to the Processing family.

The component in this framework is generally available.

Basic settings

Property type	Either Built-In or Repository.
	Built-In: No property data stored centrally.
	Repository: Select the repository file where the properties are stored.
Schema and Edit schema	A schema is a row description. It defines the number of fields (columns) to be processed and passed on to the next component. The schema is either Built-In or stored remotely in the Repository. Built-In: You create and store the schema locally for this component only. Related topic: see Talend Studio User Guide. Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. Related topic: see Talend Studio User Guide. Click Edit schema to make changes to the schema. Note that if you make changes, the schema automatically becomes built-in. View schema: choose this option to view the schema only. Change to built-in property: choose this option to change the schema to Built-in for local changes. Update repository connection: choose this option to change the schema stored in the repository and decide whether to propagate the changes to all the Jobs upon completion. If you just want to propagate the changes to the current Job, you can select No upon completion and choose this schema metadata again in the [Repository Content] window.
Read By	Select a way of extracting JSON data in the file. JsonPath: Extracts JSON data based on the JSONPath query. With this option selected, you need to select a JSONPath API version from the API version drop-down list. It is recommended to read data by JSONPath in order to gain better performance. Xpath: Extracts JSON data based on the XPath query.
JSON field	List of the JSON fields to be extracted.
Loop Jasonpath query	Enter the path pointing to the node within the JSON field, on which the loop is based. Note if you have selected Xpath from the Read by drop-down list, the Loop Xpath query field is displayed instead.
Mapping	Complete this table to map the columns defined in the schema to the corresponding JSON nodes. Column: The Column cells are automatically filled with the defined schema column names. Json query/JSONPath query: Specify the JSONPath node that holds the desired data. For more information about JSONPath expressions, see http://goessner.net/articles/JsonPath/. This column is available only when JsonPath is selected from the Read By list. XPath query: Specify the XPath node that holds the desired data. This column is available only when Xpath is selected from the Read By list. Get Nodes: Select this check box to extract the JSON data of all the nodes or select the check box next to a specific node to extract the data of that node. This column is available only when Xpath is selected from the Read By list. Is Array: select this check box when the JSON field to be extracted is an array instead of an object. This column is available only when Xpath is selected from the Read By list.
Die on error	Select the check box to stop the execution of the Job when an error occurs. Clear the check box to skip any rows on error and complete the process for error-free rows. When errors are skipped, you can collect the rows on error using a Row > Reject link.

Advanced settings

Encoding	Select the encoding from the list or select Custom and define it manually. This field is compulsory for database data handling.
tStatCatcher Statistics	Select this check box to gather the Job processing metadata at a Job level as well as at each component level.

Global Variables

Global Variables	ERROR_MESSAGE: the error message generated by the component when an error occurs. This is an After variable and it returns a string. This variable functions only if the Die on error check box is cleared, if the component has this check box. NB_LINE: the number of rows read by an input component or transferred to an output component. This is an After variable and it returns an integer. A Flow variable functions during the execution of a component while an After variable functions after the execution of the component. To fill up a field or expression with a variable, press Ctrl + Space to access the variable list and choose the variable to use from it. For further information about variables, see Talend Studio User Guide.

ERROR_MESSAGE: the error message generated by the
component when an error occurs. This is an After variable and it returns a string. This
variable functions only if the Die on error check box is
cleared, if the component has this check box.

NB_LINE: the number of rows read by an input component or
transferred to an output component. This is an After variable and it returns an
integer.

A Flow variable functions during the execution of a component while an After variable
functions after the execution of the component.

To fill up a field or expression with a variable, press Ctrl +
Space to access the variable list and choose the variable to use from it.

For further information about variables, see
Talend Studio

User Guide.

Usage

Usage rule	This component is an intermediate component. It needs an input and an output components.
Limitation	Due to license incompatibility, one or more JARs required to use this component are not provided. You can install the missing JARs for this particular component by clicking the Install button on the Component tab view. You can also find out and add all missing JARs easily on the Modules tab in the Integration perspective of your studio. You can find more details about how to install external modules in Talend Help Center (https://help.talend.com).

Usage rule

This component is an intermediate component. It needs an input and an
output components.

Limitation

Due to license incompatibility, one or more JARs required to use this component are not
provided. You can install the missing JARs for this particular component by clicking the
Install button on the Component tab view. You can also find out and add all missing JARs easily on the
Modules tab in the
Integration
perspective of your
studio. You can find more details about how to install external modules in Talend Help Center (https://help.talend.com).

Scenario 1: Retrieving error messages while extracting data from JSON fields

In this scenario, tWriteJSONField wraps the incoming
data into JSON fields, data of which is then extracted by tExtractJSONFields. Meanwhile, the error messages generated due to
extraction failure, which include the concerned JSON fields and errors, are retrieved
via a Row > Reject
link.

Linking the components

Drop the following components from the Palette onto the design workspace: tFixedFlowInput, tWriteJSONField, tExtractJSONFields, and tLogRow (X2). The two tLogRow components are renamed as data_extracted and reject_info.
Link tFixedFlowInput and tWriteJSONField using a Row > Main connection.
Link tWriteJSONField and tExtractJSONFields using a Row > Main connection.
Link tExtractJSONFields and data_extracted using a Row > Main connection.
Link tExtractJSONFields and reject_info using a Row > Reject connection.

Configuring the components

Setting up the tFixedFlowInput

Double-click tFixedFlowInput to display
its Basic settings view.
Click Edit schema to open the schema
editor.

Click the [+] button to add three
columns, namely firstname, lastname and dept, with the type of string.

Click OK to close the editor.
Select Use Inline Content and enter the
data below in the Content box:

Andrew;Wallace;Doc John;Smith;R&D Christian;Dior;Sales

1
2
3

Andrew;Wallace;Doc
John;Smith;R&D
Christian;Dior;Sales

Setting up the tWriteJSONField

Click tWriteJSONField to display its
Basic settings view.
Click Configure JSON Tree to open the XML
tree editor.

The schema of tFixedFlowInput appears in
the Linker source panel.
In the Linker target panel, click the
default rootTag and type in staff, which is the root node of the JSON field
to be generated.
Right-click staff and select Add Sub-element from the context menu.
In the pop-up box, enter the sub-node name, namely firstname.

Repeat the steps to add two more sub-nodes, namely lastname and dept.
Right-click firstname and select
Set As Loop Element from the context
menu.
Drop firstname from the Linker source panel to its counterpart in the
Linker target panel.

In the pop-up dialog box, select Add linker to
target node.

Click OK to close the dialog box.
Repeat the steps to link the two other items.

Click OK to close the XML tree
editor.
Click Edit schema to open the schema
editor.
Click the [+] button in the right panel
to add one column, namely staff, which
will hold the JSON data generated.

Click OK to close the editor.

Setting up the tExtractJSONFields

Double-click tExtractJSONFields to
display its Basic settings view.
Click Edit schema to open the schema
editor.
Click the [+] button in the right panel
to add three columns, namely firstname,
lastname and dept, which will hold the data of their counterpart nodes in
the JSON field staff.

Click OK to close the editor.
In the pop-up Propagate box, click
Yes to propagate the schema to the
subsequent components.
In the Loop XPath query field, enter
“/staff”, which is the root node of
the JSON data.
In the Mapping area, type in the node
name of the JSON data under the XPath query
part. The data of those nodes will be extracted and passed to their
counterpart columns defined in the output schema.
Specifically, define the XPath query “firstname” for the column firstname, “lastname” for
the column lastname, and “” for the column dept. Note that “” is not
a valid XPath query and will lead to execution errors.

Setting up the tLogRow components

Double-click data_extracted to display
its Basic settings view.
Select Table (print values in cells of a
table) for a better display of the results.
Perform the same setup on the other tLogRow component, namely reject_info.

Executing the Job

Press Ctrl + S to save the Job.
Click F6 to execute the Job.

As shown above, the reject row offers such details as the data extracted,
the JSON fields whose data is not extracted and the cause of the extraction
failure.

Scenario 2: Collecting data from your favorite online social network

In this scenario, tFileInputJSON retrieves the
friends node from a JSON file that contains the
data of a Facebook user and tExtractJSONFields extracts
the data from the friends node for flat data
output.

Linking the components

Drop the following components from the Palette onto the design workspace: tFileInputJSON, tExtractJSONFields and tLogRow.
Link tFileInputJSON and tExtractJSONFields using a Row > Main connection.
Link tExtractJSONFields and tLogRow using a Row > Main connection.

Configuring the components

Double-click tFileInputJSON to display
its Basic settings view.
Click Edit schema to open the schema
editor.

Click the [+] button to add one column,
namely friends, of the String
type.

Click OK to close the editor.

Click the […] button to browse for the
JSON file, facebook.json in this
case:

{ "user": { "id": "9999912398",
            "name": "Kelly Clarkson",
            "friends": [
                 { "name": "Tom Cruise",
                   "id": "55555555555555",
                   "likes": {
                       "data": [
                            { "category": "Movie",
                              "name": "The Shawshank Redemption",
                              "id": "103636093053996",
                              "created_time": "2012-11-20T15:52:07+0000"
                            },
                            { "category": "Community",
                              "name": "Positiveretribution",
                              "id": "471389562899413",
                              "created_time": "2012-12-16T21:13:26+0000"
                            }
                                ]
                            }
                 },
                 { "name": "Tom Hanks",
                   "id": "88888888888888"
                   "likes": {
                        "data": [
                            { "category": "Journalist",
                              "name": "Janelle Wang",
                              "id": "136009823148851",
                              "created_time": "2013-01-01T08:22:17+0000"
                            },
                            { "category": "Tv show",
                              "name": "Now With Alex Wagner",
                              "id": "305948749433410",
                              "created_time": "2012-11-20T06:14:10+0000"
                            }
                            ]
                           }
                  }
                        ]
          }
}

{ "user": { "id": "9999912398",

"name": "Kelly Clarkson",

"friends": [

{ "name": "Tom Cruise",

"id": "55555555555555",

"likes": {

"data": [

{ "category": "Movie",

"name": "The Shawshank Redemption",

"id": "103636093053996",

"created_time": "2012-11-20T15:52:07+0000"

{ "category": "Community",

"name": "Positiveretribution",

"id": "471389562899413",

"created_time": "2012-12-16T21:13:26+0000"

}

]

}

{ "name": "Tom Hanks",

"id": "88888888888888"

"likes": {

"data": [

{ "category": "Journalist",

"name": "Janelle Wang",

"id": "136009823148851",

"created_time": "2013-01-01T08:22:17+0000"

{ "category": "Tv show",

"name": "Now With Alex Wagner",

"id": "305948749433410",

"created_time": "2012-11-20T06:14:10+0000"

}

]

}

]

}

Clear the Read by XPath check box.

In the Mapping table, enter the JSONPath
query “$.user.friends[*]” next to the
friends column, retrieving the entire
friends node from the source
file.
Double-click tExtractJSONFields to
display its Basic settings view.
Click Edit schema to open the schema
editor.
Click the [+] button in the right panel
to add five columns, namely id, name, like_id, like_name and
like_category, which will hold the
data of relevant nodes in the JSON field friends.

Click OK to close the editor.
In the pop-up Propagate box, click
Yes to propagate the schema to the
subsequent components.
In the Loop XPath query field, enter
“/likes/data”.
In the Mapping area, type in the queries
of the JSON nodes in the XPath query
column. The data of those nodes will be extracted and passed to their
counterpart columns defined in the output schema.
Specifically, define the XPath query “../../id” (querying the “/friends/id” node) for the column id, “../../name”
(querying the “/friends/name” node) for
the column name, “id” for the column like_id, “name” for the
column like_name, and “category” for the column like_category.
Double-click tLogRow to display its
Basic settings view.
Select Table (print values in cells of a
table) for a better display of the results.

Executing the Job

Press Ctrl + S to save the Job.
Click F6 to execute the Job.

As shown above, the friends data of the Facebook user Kelly Clarkson is
extracted correctly.

tExtractJSONFields MapReduce properties

These properties are used to configure tExtractJSONFields running in the MapReduce Job framework.

The MapReduce
tExtractJSONFields component belongs to the Processing family.

The component in this framework is available only if you have subscribed to one
of the
Talend
solutions with Big Data.

Basic settings

Property type	Either Built-In or Repository.
	Built-In: No property data stored centrally.
	Repository: Select the repository file where the properties are stored.
Schema and Edit Schema	A schema is a row description. It defines the number of fields (columns) to be processed and passed on to the next component. The schema is either Built-In or stored remotely in the Repository. Click Edit schema to make changes to the schema. If the current schema is of the Repository type, three options are available: View schema: choose this option to view the schema only. Change to built-in property: choose this option to change the schema to Built-in for local changes. Update repository connection: choose this option to change the schema stored in the repository and decide whether to propagate the changes to all the Jobs upon completion. If you just want to propagate the changes to the current Job, you can select No upon completion and choose this schema metadata again in the [Repository Content] window.
	Built-In: You create and store the schema locally for this component only. Related topic: see Talend Studio User Guide.
	Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. Related topic: see Talend Studio User Guide.
Read by	Select a way of extracting the JSON data in the file. Xpath: Extracts the JSON data based on the XPath query. JsonPath: Extracts the JSON data based on the JSONPath query. Note that it is recommended to read the data by JSONPath in order to gain better performance.
JSON field	List of the JSON fields to be extracted.
Loop Jasonpath query	Enter the path pointing to the node within the JSON field, on which the loop is based. Note if you have selected Xpath from the Read by drop-down list, the Loop Xpath query field is displayed instead.
Mapping	Complete this table to map the columns defined in the schema to the corresponding JSON nodes. Column: The Column cells are automatically filled with the defined schema column names. Json query/JSONPath query: Specify the JSONPath node that holds the desired data. For more information about JSONPath expressions, see http://goessner.net/articles/JsonPath/. This column is available only when JsonPath is selected from the Read By list. XPath query: Specify the XPath node that holds the desired data. This column is available only when Xpath is selected from the Read By list. Get Nodes: Select this check box to extract the JSON data of all the nodes or select the check box next to a specific node to extract the data of that node. This column is available only when Xpath is selected from the Read By list. Is Array: select this check box when the JSON field to be extracted is an array instead of an object. This column is available only when Xpath is selected from the Read By list.
Die on error	Select the check box to stop the execution of the Job when an error occurs. Clear the check box to skip any rows on error and complete the process for error-free rows. When errors are skipped, you can collect the rows on error using a Row > Reject link.

Advanced settings

Encoding	Select the encoding from the list or select Custom and define it manually. This field is compulsory for database data handling.

Global Variables

Global Variables	ERROR_MESSAGE: the error message generated by the component when an error occurs. This is an After variable and it returns a string. This variable functions only if the Die on error check box is cleared, if the component has this check box. NB_LINE: the number of rows read by an input component or transferred to an output component. This is an After variable and it returns an integer. A Flow variable functions during the execution of a component while an After variable functions after the execution of the component. To fill up a field or expression with a variable, press Ctrl + Space to access the variable list and choose the variable to use from it. For further information about variables, see Talend Studio User Guide.

NB_LINE: the number of rows read by an input component or
transferred to an output component. This is an After variable and it returns an
integer.

A Flow variable functions during the execution of a component while an After variable
functions after the execution of the component.

To fill up a field or expression with a variable, press Ctrl +
Space to access the variable list and choose the variable to use from it.

For further information about variables, see
Talend Studio

User Guide.

Usage

Usage rule	In a Talend Map/Reduce Job, this component is used as an intermediate step and other components used along with it must be Map/Reduce components, too. They generate native Map/Reduce code that can be executed directly in Hadoop. You need to use the Hadoop Configuration tab in the Run view to define the connection to a given Hadoop distribution for the whole Job. For further information about a Talend Map/Reduce Job, see the sections describing how to create, convert and configure a Talend Map/Reduce Job of the Talend Open Studio for Big Data Getting Started Guide . Note that in this documentation, unless otherwise explicitly stated, a scenario presents only Standard Jobs, that is to say traditional Talend data integration Jobs, and non Map/Reduce Jobs.

Usage rule

In a
Talend
Map/Reduce Job, this component is used as an intermediate
step and other components used along with it must be Map/Reduce components, too. They
generate native Map/Reduce code that can be executed directly in Hadoop.

You need to use the Hadoop Configuration tab in the
Run view to define the connection to a given Hadoop
distribution for the whole Job.

For further information about a
Talend
Map/Reduce Job, see the sections
describing how to create, convert and configure a
Talend
Map/Reduce Job of the

Talend Open Studio for Big Data Getting Started
Guide
.

Note that in this documentation, unless otherwise
explicitly stated, a scenario presents only Standard Jobs,
that is to say traditional
Talend
data integration Jobs, and non Map/Reduce Jobs.

Related scenarios

No scenario is available for the Map/Reduce version of this component yet.

tExtractJSONFields properties for Apache Spark Batch

These properties are used to configure tExtractJSONFields running in the Spark Batch Job framework.

The Spark Batch
tExtractJSONFields component belongs to the Processing family.

The component in this framework is available only if you have subscribed to one
of the
Talend
solutions with Big Data.

Basic settings

Property type	Either Built-In or Repository.
	Built-In: No property data stored centrally.
	Repository: Select the repository file where the properties are stored.
Schema and Edit Schema	A schema is a row description. It defines the number of fields (columns) to be processed and passed on to the next component. The schema is either Built-In or stored remotely in the Repository. Click Edit schema to make changes to the schema. If the current schema is of the Repository type, three options are available: View schema: choose this option to view the schema only. Change to built-in property: choose this option to change the schema to Built-in for local changes. Update repository connection: choose this option to change the schema stored in the repository and decide whether to propagate the changes to all the Jobs upon completion. If you just want to propagate the changes to the current Job, you can select No upon completion and choose this schema metadata again in the [Repository Content] window.
	Built-In: You create and store the schema locally for this component only. Related topic: see Talend Studio User Guide.
	Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. Related topic: see Talend Studio User Guide.
Read by	Select a way of extracting the JSON data in the file. Xpath: Extracts the JSON data based on the XPath query. JsonPath: Extracts the JSON data based on the JSONPath query. Note that it is recommended to read the data by JSONPath in order to gain better performance.
JSON field	List of the JSON fields to be extracted.
Loop Jasonpath query	Enter the path pointing to the node within the JSON field, on which the loop is based. Note if you have selected Xpath from the Read by drop-down list, the Loop Xpath query field is displayed instead.
Mapping	Complete this table to map the columns defined in the schema to the corresponding JSON nodes. Column: The Column cells are automatically filled with the defined schema column names. Json query/JSONPath query: Specify the JSONPath node that holds the desired data. For more information about JSONPath expressions, see http://goessner.net/articles/JsonPath/. This column is available only when JsonPath is selected from the Read By list. XPath query: Specify the XPath node that holds the desired data. This column is available only when Xpath is selected from the Read By list. Get Nodes: Select this check box to extract the JSON data of all the nodes or select the check box next to a specific node to extract the data of that node. This column is available only when Xpath is selected from the Read By list. Is Array: select this check box when the JSON field to be extracted is an array instead of an object. This column is available only when Xpath is selected from the Read By list.
Die on error	Select the check box to stop the execution of the Job when an error occurs.

Advanced settings

Encoding	Select the encoding from the list or select Custom and define it manually. This field is compulsory for database data handling.

Usage

Usage rule	This component is used as an intermediate step. This component, along with the Spark Batch component Palette it belongs to, appears only when you are creating a Spark Batch Job. Note that in this documentation, unless otherwise explicitly stated, a scenario presents only Standard Jobs, that is to say traditional Talend data integration Jobs.
Spark Connection	You need to use the Spark Configuration tab in the Run view to define the connection to a given Spark cluster for the whole Job. In addition, since the Job expects its dependent jar files for execution, you must specify the directory in the file system to which these jar files are transferred so that Spark can access these files: Yarn mode: when using Google Dataproc, specify a bucket in the Google Storage staging bucket field in the Spark configuration tab; when using other distributions, use a tHDFSConfiguration component to specify the directory. Standalone mode: you need to choose the configuration component depending on the file system you are using, such as tHDFSConfiguration or tS3Configuration. This connection is effective on a per-Job basis.

Usage rule

This component is used as an intermediate step.

This component, along with the Spark Batch component Palette it belongs to, appears only
when you are creating a Spark Batch Job.

Note that in this documentation, unless otherwise
explicitly stated, a scenario presents only Standard Jobs,
that is to say traditional
Talend
data integration Jobs.

Spark Connection

You need to use the Spark Configuration tab in
the Run view to define the connection to a given
Spark cluster for the whole Job. In addition, since the Job expects its dependent jar
files for execution, you must specify the directory in the file system to which these
jar files are transferred so that Spark can access these files:

Yarn mode: when using Google
Dataproc, specify a bucket in the Google Storage staging
bucket field in the Spark
configuration tab; when using other distributions, use a
tHDFSConfiguration
component to specify the directory.
Standalone mode: you need to choose
the configuration component depending on the file system you are using, such
as tHDFSConfiguration
or tS3Configuration.

This connection is effective on a per-Job basis.

Related scenarios

No scenario is available for the Spark Batch version of this component
yet.

tExtractJSONFields properties for Apache Spark Streaming

These properties are used to configure tExtractJSONFields running in the Spark Streaming Job framework.

The Spark Streaming
tExtractJSONFields component belongs to the Processing family.

The component in this framework is available only if you have subscribed to Talend Real-time Big Data Platform or Talend Data
Fabric.

Basic settings

Property type	Either Built-In or Repository.
	Built-In: No property data stored centrally.
	Repository: Select the repository file where the properties are stored.
Schema and Edit Schema	A schema is a row description. It defines the number of fields (columns) to be processed and passed on to the next component. The schema is either Built-In or stored remotely in the Repository. Click Edit schema to make changes to the schema. If the current schema is of the Repository type, three options are available: View schema: choose this option to view the schema only. Change to built-in property: choose this option to change the schema to Built-in for local changes. Update repository connection: choose this option to change the schema stored in the repository and decide whether to propagate the changes to all the Jobs upon completion. If you just want to propagate the changes to the current Job, you can select No upon completion and choose this schema metadata again in the [Repository Content] window.
	Built-In: You create and store the schema locally for this component only. Related topic: see Talend Studio User Guide.
	Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. Related topic: see Talend Studio User Guide.
Read by	Select a way of extracting the JSON data in the file. Xpath: Extracts the JSON data based on the XPath query. JsonPath: Extracts the JSON data based on the JSONPath query. Note that it is recommended to read the data by JSONPath in order to gain better performance.
JSON field	List of the JSON fields to be extracted.
Loop Jasonpath query	Enter the path pointing to the node within the JSON field, on which the loop is based. Note if you have selected Xpath from the Read by drop-down list, the Loop Xpath query field is displayed instead.
Mapping	Complete this table to map the columns defined in the schema to the corresponding JSON nodes. Column: The Column cells are automatically filled with the defined schema column names. Json query/JSONPath query: Specify the JSONPath node that holds the desired data. For more information about JSONPath expressions, see http://goessner.net/articles/JsonPath/. This column is available only when JsonPath is selected from the Read By list. XPath query: Specify the XPath node that holds the desired data. This column is available only when Xpath is selected from the Read By list. Get Nodes: Select this check box to extract the JSON data of all the nodes or select the check box next to a specific node to extract the data of that node. This column is available only when Xpath is selected from the Read By list. Is Array: select this check box when the JSON field to be extracted is an array instead of an object. This column is available only when Xpath is selected from the Read By list.
Die on error	Select the check box to stop the execution of the Job when an error occurs.

Advanced settings

Encoding	Select the encoding from the list or select Custom and define it manually. This field is compulsory for database data handling.

Usage

Usage rule	This component is used as an intermediate step. This component, along with the Spark Streaming component Palette it belongs to, appears only when you are creating a Spark Streaming Job. Note that in this documentation, unless otherwise explicitly stated, a scenario presents only Standard Jobs, that is to say traditional Talend data integration Jobs.
Spark Connection	You need to use the Spark Configuration tab in the Run view to define the connection to a given Spark cluster for the whole Job. In addition, since the Job expects its dependent jar files for execution, you must specify the directory in the file system to which these jar files are transferred so that Spark can access these files: Yarn mode: when using Google Dataproc, specify a bucket in the Google Storage staging bucket field in the Spark configuration tab; when using other distributions, use a tHDFSConfiguration component to specify the directory. Standalone mode: you need to choose the configuration component depending on the file system you are using, such as tHDFSConfiguration or tS3Configuration. This connection is effective on a per-Job basis.

Usage rule

This component is used as an intermediate step.

This component, along with the Spark Streaming component Palette it belongs to, appears
only when you are creating a Spark Streaming Job.

Note that in this documentation, unless otherwise explicitly stated, a scenario presents
only Standard Jobs, that is to say traditional
Talend
data
integration Jobs.

Spark Connection

Yarn mode: when using Google
Dataproc, specify a bucket in the Google Storage staging
bucket field in the Spark
configuration tab; when using other distributions, use a
tHDFSConfiguration
component to specify the directory.
Standalone mode: you need to choose
the configuration component depending on the file system you are using, such
as tHDFSConfiguration
or tS3Configuration.

This connection is effective on a per-Job basis.

Related scenarios

For a related scenario, see Analyzing a Twitter flow in near real-time.

tExtractJSONFields Storm properties

These properties are used to configure tExtractJSONFields running in the Storm Job framework.

The Storm
tExtractJSONFields component belongs to the Processing family.

The component in this framework is available only if you have subscribed to Talend Real-time Big Data Platform or Talend Data
Fabric.

Basic settings

Property type	Either Built-In or Repository.
	Built-In: No property data stored centrally.
	Repository: Select the repository file where the properties are stored.
Schema and Edit Schema	A schema is a row description. It defines the number of fields (columns) to be processed and passed on to the next component. The schema is either Built-In or stored remotely in the Repository. Click Edit schema to make changes to the schema. If the current schema is of the Repository type, three options are available: View schema: choose this option to view the schema only. Change to built-in property: choose this option to change the schema to Built-in for local changes. Update repository connection: choose this option to change the schema stored in the repository and decide whether to propagate the changes to all the Jobs upon completion. If you just want to propagate the changes to the current Job, you can select No upon completion and choose this schema metadata again in the [Repository Content] window.
	Built-In: You create and store the schema locally for this component only. Related topic: see Talend Studio User Guide.
	Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. Related topic: see Talend Studio User Guide.
JSON field	List of the JSON fields to be extracted.
Loop XPath query	Node within the JSON field, on which the loop is based.
Mapping	Column: schema defined to hold the data extracted from the JSON field. XPath Query: XPath Query to specify the node within the JSON field. Get nodes: select this check box to extract the JSON data of all the nodes specified in the XPath query list or select the check box next to a specific node to extract its JSON data only. Is Array: select this check box when the JSON field to be extracted is an array instead of an object.

Advanced settings

Encoding	Select the encoding from the list or select Custom and define it manually. This field is compulsory for database data handling.

Usage

Usage rule	If you have subscribed to one of the Talend solutions with Big Data, you can also use this component as a Storm component. In a Talend Storm Job, this component is used as an intermediate step and other components used along with it must be Storm components, too. They generate native Storm code that can be executed directly in a Storm system. The Storm version does not support the use of the global variables. You need to use the Storm Configuration tab in the Run view to define the connection to a given Storm system for the whole Job. This connection is effective on a per-Job basis. For further information about a Talend Storm Job, see the sections describing how to create and configure a Talend Storm Job of the Talend Open Studio for Big Data Getting Started Guide . Note that in this documentation, unless otherwise explicitly stated, a scenario presents only Standard Jobs, that is to say traditional Talend data integration Jobs.

Usage rule

If you have subscribed to one of the
Talend
solutions with Big Data, you can also
use this component as a Storm component. In a
Talend
Storm Job, this component is used as
an intermediate step and other components used along with it must be Storm components, too.
They generate native Storm code that can be executed directly in a Storm system.

The Storm version does not support the use of the global variables.

You need to use the Storm Configuration tab in the
Run view to define the connection to a given Storm
system for the whole Job.

This connection is effective on a per-Job basis.

For further information about a
Talend
Storm Job, see the sections
describing how to create and configure a
Talend
Storm Job of the
Talend Open Studio for Big Data Getting Started
Guide
.

Note that in this documentation, unless otherwise explicitly stated, a scenario presents
only Standard Jobs, that is to say traditional
Talend
data
integration Jobs.

Related scenarios

No scenario is available for the Storm version of this component
yet.

Document get from Talend https://help.talend.com

Thank you for watching.

Docs 6.x

0 Comments

Inline Feedbacks

View all comments