August 15, 2023

tFileStreamInputXML – Docs for ESB 6.x

tFileStreamInputXML

Opens a structured XML file and reads it row by row to split the data into fields,
then sends these fields as defined in the Schema to the next component.

tFileStreamInputXML properties for Apache Spark Streaming

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

The Spark Streaming
tFileStreamInputXML component belongs to the File family.

The streaming version of this component is available in the Palette of the Studio only if you have subscribed to Talend Real-time Big Data Platform or Talend Data
Fabric.

Basic settings

Define a storage configuration
component

Select the configuration component to be used to provide the configuration
information for the connection to the target file system such as HDFS.

If you leave this check box clear, the target file system is the local
system.

The configuration component to be used must be present in the same Job. For
example, if you have dropped a tHDFSConfiguration component in the Job, you can select it to write
the result in a given HDFS system.

Property type

Either Built-In or Repository.

 

Built-In: No property data stored centrally.

 

Repository: Select the repository file where the
properties are stored.

The properties are stored centrally under the Hadoop
Cluster
node of the Repository
tree.

The fields that come after are pre-filled in using the fetched
data.

For further information about the Hadoop
Cluster
node, see the Getting Started Guide.

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.

Folder/File

Browse to, or enter the path pointing to the data to be used in the file system.

If the path you set points to a folder, this component will read all of the files stored in that folder, for example, /user/talend/in; if sub-folders exist, the sub-folders are automatically ignored unless you define the property
spark.hadoop.mapreduce.input.fileinputformat.input.dir.recursive to be true in the Advanced properties table in the Spark configuration tab.

If you want to specify more than one files or directories in this
field, separate each path using a comma (,).

If the file to be read is a compressed one, enter the file name
with its extension; then ttFileInputXML automatically decompresses it at
runtime. The supported compression formats and their corresponding
extensions are:

  • DEFLATE: *.deflate

  • gzip: *.gz

  • bzip2: *.bz2

  • LZO: *.lzo

The button for browsing does not work with the Spark Local mode; if you are using the Spark Yarn or the Spark Standalone mode,
ensure that you have properly configured the connection in a configuration component in
the same Job, such as tHDFSConfiguration.

Element to extract

Enter the element from which you need to read the contents and the
child elements of the input XML data.

The element defined in this field is used at the root node of any
XPath specified within this component. This element helps define the
atomic units of the XML data to be used so that however big the
original document is or wherever the input is split, the rows within
this element can be correctly distributed to the mapper
tasks.

Note that any content outside this element is ignored and the
child elements of this element cannot contain this element
itself.

Loop XPath query

Node of the tree, which the loop is based on.

Note its root is the element you have defined in the Element to extract field.

Mapping

Column: Columns to map. They
reflect the schema as defined in the Schema type field.

XPath Query: Enter the fields to
be extracted from the structured input.

Get nodes: Select this check box
to recuperate the XML content of all current nodes specified in the
Xpath query list, or select the
check box next to specific XML nodes to recuperate only the content
of the selected nodes. These nodes are important when the output
flow from this component needs to use the XML structure, for
example, the Document data
type.

For further information about the Document type, see

Talend Studio User
Guide
.

Die on error

Select the check box to stop the execution of the Job when an error
occurs.

Advanced settings

Custom encoding

You may encounter encoding issues when you process the stored data. In that
situation, select this check box to display the Encoding list.

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 a start component and requires an output link.

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.

Related scenarios

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


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