tHDFSOutputRaw Standard properties

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. When you create a Spark Job, avoid the reserved word line when naming the fields.

The schema of this component is read-only. You can click Edit schema to view the schema.

• 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.

Use an existing connection

Select this check box and in the Component List click the HDFS connection component from which you want to reuse the connection details already defined.

Note that when a Job contains the parent Job and the child Job, Component List presents only the connection components in the same Job level.

Distribution

1. Select Import from existing version to import an officially supported distribution as base and then add other required jar files which the base distribution does not provide.

2. Select Import from zip to import the configuration zip for the custom distribution to be used. This zip file should contain the libraries of the different Hadoop elements and the index file of these libraries.

   Note that custom versions are not officially supported by Talend . Talend and its community provide you with the opportunity to connect to custom versions from the Studio but cannot guarantee that the configuration of whichever version you choose will be easy, due to the wide range of different Hadoop distributions and versions that are available. As such, you should only attempt to set up such a connection if you have sufficient Hadoop experience to handle any issues on your own.

   Information noteNote:

   In this dialog box, the active check box must be kept selected so as to import the jar files pertinent to the connection to be created between the custom distribution and this component.

   For a step-by-step example about how to connect to a custom distribution and share this connection, see Hortonworks.

Version

Select the version of the Hadoop distribution you are using. The available options vary depending on the component you are using.

• HDFS
• WebHDFS. WebHDFS with SSL is not supported yet.
• ADLS. Only Azure Data Lake Storage Gen1 is supported.

The schemes present on this list vary depending on the distribution you are using and only the scheme that appears on this list with a given distribution is officially supported by Talend.

Once a scheme is selected, the corresponding syntax such as webhdfs://localhost:50070/ for WebHDFS is displayed in the field for the NameNode location of your cluster.

NameNode URI

Type in the URI of the Hadoop NameNode, the master node of a Hadoop system. For example, we assume that you have chosen a machine called masternode as the NameNode, then the location is hdfs://masternode:portnumber. If you are using WebHDFS, the location should be webhdfs://masternode:portnumber; WebHDFS with SSL is not supported yet.

Use kerberos authentication

This check box is available depending on the Hadoop distribution you are connecting to.

Select the Use a keytab to authenticate check box to log into a Kerberos-enabled system using a given keytab file. A keytab file contains pairs of Kerberos principals and encrypted keys. You need to enter the principal to be used in the Principal field and the access path to the keytab file itself in the Keytab field. This keytab file must be stored in the machine in which your Job actually runs, for example, on a Talend Jobserver.

Note that the user that executes a keytab-enabled Job is not necessarily the one a principal designates but must have the right to read the keytab file being used. For example, the username you are using to execute a Job is user1 and the principal to be used is guest; in this situation, ensure that user1 has the right to read the keytab file to be used.

Use Datanode hostname

Select the Use datanode hostname check box to allow the Job to access datanodes via their hostnames. This actually sets the dfs.client.use.datanode.hostname property to true. When connecting to a S3N filesystem, you must select this check box.

User name

The User name field is available when you are not using Kerberos to authenticate. In the User name field, enter the login username for your distribution. If you leave it empty, the username of the machine hosting the Studio will be used.

Group

Enter the membership including the authentication user under which the HDFS instances were started. This field is available depending on the distribution you are using.

File Name

Browse to, or enter the location of the file which you write data to. This file is created automatically if it does not exist.

Action

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. The supported encodings depend on the JVM that you are using. For more information, see https://docs.oracle.com.

This option is not available for a Sequence file.

Compression

Select the Compress the data check box to compress the output data.

Hadoop provides different compression formats that help reduce the space needed for storing files and speed up data transfer. When reading a compressed file, the Studio needs to uncompress it before being able to feed it to the input flow.

Note that when the type of the file to be written is Sequence File, the compression algorithm is embedded within the container files (the part- files) of this sequence file. These files can be read by a Talend component such as tHDFSInput within MapReduce Jobs and other applications that understand the sequence file format. Alternatively, when the type is Text File, the output files can be accessed with standard compression utilities that understand the bzip2 or gzip container files.

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.

Hadoop properties

tStatCatcher Statistics

Select this check box to collect log data at the component level.

Global Variables

FILENAME_PATH: the path of the input file. This is an After variable and it returns a string.

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.

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 rule

This component needs an input component that provides the data of a single column. This column must be labeled to content and its type must be Object.

For example, you can:

• use tHMap to provide this single column,
• use tConvertType to convert a column from String to Object, or
• use tJavaRow to add the data to be processed into the globalMap object so that this data becomes available as a global variable for the other components such as tFixedFlowInput to construct this required single column.

For further information about tHMap, see tHMap.

For further information about tConvertType, see tConvertType.

For further information about tJavaRow, see tJavaRow.

For further information about tFixedFlowInput, see tFixedFlowInput.

For further information about how to use a global variable, see the section describing how to use contexts and variables in Talend Studio User Guide.

Dynamic settings

Click the [+] button to add a row in the table and fill the Code field with a context variable to choose your HDFS connection dynamically from multiple connections planned in your Job. This feature is useful when you need to access files in different HDFS systems or different distributions, especially when you are working in an environment where you cannot change your Job settings, for example, when your Job has to be deployed and executed independent of Talend Studio .

The Dynamic settings table is available only when the Use an existing connection check box is selected in the Basic settings view. Once a dynamic parameter is defined, the Component List box in the Basic settings view becomes unusable.

For examples on using dynamic parameters, see Reading data from databases through context-based dynamic connections and Reading data from different MySQL databases using dynamically loaded connection parameters. For more information on Dynamic settings and context variables, see Talend Studio User Guide.

Prerequisites

The Hadoop distribution must be properly installed, so as to guarantee the interaction with Talend Studio . The following list presents MapR related information for example.

• Ensure that you have installed the MapR client in the machine where the Studio is, and added the MapR client library to the PATH variable of that machine. According to MapR's documentation, the library or libraries of a MapR client corresponding to each OS version can be found under MAPR_INSTALL\ hadoop\hadoop-VERSION\lib\native. For example, the library for Windows is \lib\native\MapRClient.dll in the MapR client jar file. For further information, see the following link from MapR: http://www.mapr.com/blog/basic-notes-on-configuring-eclipse-as-a-hadoop-development-environment-for-mapr.

  Without adding the specified library or libraries, you may encounter the following error: no MapRClient in java.library.path.

• Set the -Djava.library.path argument, for example, in the Job Run VM arguments area of the Run/Debug view in the Preferences dialog box in the Window menu. This argument provides to the Studio the path to the native library of that MapR client. This allows the subscription-based users to make full use of the Data viewer to view locally in the Studio the data stored in MapR.

For further information about how to install a Hadoop distribution, see the manuals corresponding to the Hadoop distribution you are using.