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tHiveCreateTable Standard properties

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

The Standard tHiveCreateTable component belongs to the Big Data and the Databases families.

The component in this framework is available in all Talend products with Big Data and in Talend Data Fabric.

Basic settings

Connection configuration:

  • When you use this component with Google Dataproc:

    Project ID

    Enter the ID of your Google Cloud Platform project.

    If you are not certain about your project ID, confirm it in the Manage Resources page of your Google Cloud Platform services.

    Cluster ID

    Enter the ID of your Dataproc cluster to be used.
    Region

    From this drop-down list, select the Google Cloud region to be used.
    Google Storage staging bucket

    As a Talend Job expects its dependent jar files for execution, specify the Google Storage directory to which these jar files are transferred so that your Job can access these files at execution.

    The directory to be entered must end with a slash (/). If not existing, the directory is created on the fly but the bucket to be used must already exist.

    Database

    Fill this field with the name of the database.

    Provide Google Credentials in file

    Leave this check box clear, when you launch your Job from a given machine in which Google Cloud SDK has been installed and authorized to use your user account credentials to access Google Cloud Platform. In this situation, this machine is often your local machine.

    When you launch your Job from a remote machine, such as a Talend JobServer, select this check box and in the Path to Google Credentials file field that is displayed, enter the directory in which this JSON file is stored in the Talend JobServer machine. You can also click the [...] button, and then in the pop-up dialog box, browse for the JSON file.

    For further information about this Google Credentials file, see the administrator of your Google Cloud Platform or visit Google Cloud Platform Auth Guide.

  • When you use this component with Microsoft HDInsight distribution:

    Livy configuration

    Enter the address and the authentication information of the Microsoft HD Insight cluster to be used. For example, the address could be https://your_hdinsight_cluster_name.azurehdinsight.net and the authentication information is your Azure account name: yourname. Talend Studio uses this service to submit the Job to the HD Insight cluster.

    In the Job result folder field, enter the location in which you want to store the execution result of a Job in the Azure Storage to be used.

    Job status polling configuration

    In the Poll interval when retrieving Job status (in ms) field, enter the time interval (in milliseconds) at the end of which you want Talend Studio to ask Spark for the status of your Job. For example, this status could be Pending or Running.

    In the Maximum number of consecutive statuses missing field, enter the maximum number of times Talend Studio should retry to get a status when there is no status response.

    HDInsight configuration

    • The Username is the one defined when creating your cluster. You can find it in the SSH + Cluster login blade of your cluster.
    • The Password is defined when creating your HDInsight cluster for authentication to this cluster.

    Windows Azure Storage configuration

    Enter the address and the authentication information of the Azure Storage or ADLS Gen2 account to be used. In this configuration, you do not define where to read or write your business data but define where to deploy your Job only.

    In the Container field, enter the name of the container to be used. You can find the available containers in the Blob blade of the Azure Storage account to be used.

    In the Deployment Blob field, enter the location in which you want to store the current Job and its dependent libraries in this Azure Storage account.

    In the Hostname field, enter the Primary Blob Service Endpoint of your Azure Storage account without the https:// part. You can find this endpoint in the Properties blade of this storage account.

    In the Username field, enter the name of the Azure Storage account to be used.

    In the Password field, enter the access key of the Azure Storage account to be used. This key can be found in the Access keys blade of this storage account.

    Database

    Fill this field with the name of the database.

  • When you use the other distributions:

    Connection mode

    Select a connection mode from the list. The options vary depending on the distribution you are using.

    Hive version

    Select the Hive version you are using.

    Host

    Database server IP address.

    Port

    Listening port number of DB server.

    Database

    Fill this field with the name of the database.

    Username and Password

    DB user authentication data.

    To enter the password, click the [...] button next to the password field, enter the password in double quotes in the pop-up dialog box, and click OK to save the settings.

    Use kerberos authentication

    If you are accessing a Hive metastore running with Kerberos security, select this check box and then enter the relevant parameters in the fields that appear.

    The values of the following parameters can be found in the hive-site.xml file of the Hive system to be used.

    1. Hive principal uses the value of hive.metastore.kerberos.principal. This is the service principal of the Hive metastore.

    2. HiveServer2 local user principal uses the value of hive.server2.authentication.kerberos.principal.

    3. HiveServer2 local user keytab uses the value of hive.server2.authentication.kerberos.keytab

    4. Metastore URL uses the value of javax.jdo.option.ConnectionURL. This is the JDBC connection string to the Hive metastore.

    5. Driver class uses the value of javax.jdo.option.ConnectionDriverName. This is the name of the driver for the JDBC connection.

    6. Username uses the value of javax.jdo.option.ConnectionUserName. This, as well as the Password parameter, is the user credential for connecting to the Hive Metastore.

    7. Password uses the value of javax.jdo.option.ConnectionPassword.

    For the other parameters that are displayed, consult the Hadoop configuration files they belong to. For example, the Namenode principal can be found in the hdfs-site.xml file or the hdfs-default.xml file of the distribution you are using.

    This check box is available depending on the Hadoop distribution you are connecting to.
    Use a keytab to authenticate

    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 SSL encryption

    Select this check box to enable the SSL or TLS encrypted connection.

    Then in the fields that are displayed, provide the authentication information:

    • In the Trust store path field, enter the path, or browse to the TrustStore file to be used. By default, the supported TrustStore types are JKS and PKCS 12.

    • To enter the password, click the [...] button next to the password field, enter the password in double quotes in the pop-up dialog box, and click OK to save the settings.

    This feature is available only to the HiveServer2 in the Standalone mode of the following distributions:

    • Hortonworks Data Platform 2.0 +

    • Cloudera CDH4 +

    • Pivotal HD 2.0 +

    • Amazon EMR 4.0.0 +

    Set Resource Manager

    Select this check box and in the displayed field, enter the location of the ResourceManager of your distribution. For example, tal-qa114.talend.lan:8050.

    Then you can continue to set the following parameters depending on the configuration of the Hadoop cluster to be used (if you leave the check box of a parameter clear, then at runtime, the configuration about this parameter in the Hadoop cluster to be used will be ignored ):

    1. Select the Set resourcemanager scheduler address check box and enter the Scheduler address in the field that appears.

    2. Select the Set jobhistory address check box and enter the location of the JobHistory server of the Hadoop cluster to be used. This allows the metrics information of the current Job to be stored in that JobHistory server.

    3. Select the Set staging directory check box and enter this directory defined in your Hadoop cluster for temporary files created by running programs. Typically, this directory can be found under the yarn.app.mapreduce.am.staging-dir property in the configuration files such as yarn-site.xml or mapred-site.xml of your distribution.

    4. Allocate proper memory volumes to the Map and the Reduce computations and the ApplicationMaster of YARN by selecting the Set memory check box in the Advanced settings view.

    5. Select the Set Hadoop user check box and enter the user name under which you want to execute the Job. Since a file or a directory in Hadoop has its specific owner with appropriate read or write rights, this field allows you to execute the Job directly under the user name that has the appropriate rights to access the file or directory to be processed.

    6. 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.

    For further information about these parameters, see the documentation or contact the administrator of the Hadoop cluster to be used.

    For further information about the Hadoop Map/Reduce framework, see the Map/Reduce tutorial in Apache's Hadoop documentation.

    Set NameNode URI

    Select this check box and in the displayed field, enter the URI of the Hadoop NameNode, the master node of a Hadoop system. For example, assuming 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.

    For further information about the Hadoop Map/Reduce framework, see the Map/Reduce tutorial in Apache's Hadoop documentation.

    Spark catalog

    Select the Spark implementation to use.
    • In-memory: select this value if you set the Hive thrift metastore to a Hive metastore that is not an external metastore.
    • Hive: select this value if you set the Hive thrift metastore to an external Hive metastore that exists outside of your cluster.

The other properties:

Property type

Either Built-in or Repository.

 

Built-in: No property data stored centrally.

 

Repository: Select the repository file in which the properties are stored. The fields that follow are completed automatically using the data retrieved.

Use an existing connection

Select this check box and in the Component List drop-down list, select the desired connection component to reuse the connection details you already defined.

Information noteNote: When a Job contains the parent Job and the child Job, do the following if you want to share an existing connection between the parent Job and the child Job (for example, to share the connection created by the parent Job with the child Job).
  1. In the parent level, register the database connection to be shared in the Basic settings view of the connection component which creates that very database connection.
  2. In the child level, use a dedicated connection component to read that registered database connection.

For an example about how to share a database connection across Job levels, see Sharing a database connection.

Distribution

Select the cluster you are using from the drop-down list. The options in the list vary depending on the component you are using. Among these options, the following ones requires specific configuration:

  • If available in this Distribution drop-down list, the Microsoft HD Insight option allows you to use a Microsoft HD Insight cluster. For this purpose, you need to configure the connections to the HD Insight cluster and the Windows Azure Storage service of that cluster in the areas that are displayed. For detailed explanation about these parameters, see Configuring the connection manually.

  • If you select Amazon EMR, find more details in Amazon EMR - Getting Started.

  • The Custom option allows you to connect to a cluster different from any of the distributions given in this list, that is to say, to connect to a cluster not officially supported by Talend .

  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 Talend 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.

Information noteNote: From Talend Studio 8.0 R2024-04 onwards, the Distribution parameter has been removed.

Hive version

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

Information noteNote: From Talend Studio 8.0 R2024-04 onwards, the Hive version parameter has been removed.
Hiver Server Select the Hive version you are using.
Hadoop version Select the Hadoop version you are using.

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.

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.

 

Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs.

When the schema to be reused has default values that are integers or functions, ensure that these default values are not enclosed within quotation marks. If they are, you must remove the quotation marks manually.

For more information, see Retrieving table schemas.

Table Name

Name of the table to be created.

Action on table

Select the action to be carried out for creating a table.

Format

Select the data format to which the table to be created is dedicated.

The available data formats vary depending on the version of the Hadoop distribution you are using.

Note that when the file format to be used is PARQUET, you might be prompted to find the specific PARQUET JAR file and install it into Talend Studio.

  • When the connection mode to Hive is Embedded, the Job is run in your local machine and calls this JAR installed in Talend Studio.

  • When the connection mode to Hive is Standalone, the Job is run in the server hosting Hive and this JAR file is sent to the HDFS system of the cluster you are connecting to. Therefore, ensure that you have correctly defined the NameNode URI in the corresponding field of the Basic settings view.

This JAR file can be downloaded from Apache's site. For details about how to install external modules, see Installing external modules.

Inputformat class and Outputformat class

These fields appear only when you have selected INPUTFORMAT and OUTPUTFORMAT from the Format list.

These fields allow you to enter the name of the jar files to be used for the data formats not available in the Format list.

Storage class

Enter the name of the storage handler to be used for creating a non-native table (Hive table stored and managed in other systems than Hive, for example, Cassandra or MongoDB).

This field is available only when you have selected STORAGE from the Format list.

For further information about a storage handler, see Hive Storage Handlers.
Set partitions

Select this check box to add partition columns to the table to be created. Once selecting it, you need to define the schema of the partition columns you need to add.

Set file location

If you want to create a Hive table in a directory other than the default one, select this check box and enter the directory in HDFS you want to use to hold the table content.

This is typical useful when you need to create an external Hive table by selecting the Create an external table check box in the Advanced settings tab.

Use S3 endpoint

The Use S3 endpoint check box is displayed when you have selected the Set file location check box to create an external Hive table.

Once this Use S3 endpoint check box is selected, you need to enter the following parameters in the fields that appear:

  • S3 bucket: enter the name of the bucket in which you need to create the table.

  • Bucket name: enter the name of the bucket in which you want to store the dependencies of your Job. This bucket must already exist on S3.
  • Temporary resource folder: enter the directory in which you want to store the dependencies of your Job. For example, enter temp_resources to write the dependencies in the /temp_resources folder in the bucket.

    If this folder already exists at runtime, its contents are overwritten by the upcoming dependencies; otherwise, this folder is automatically created.

  • Access key and Secret key: enter the authentication information required to connect to the Amazon S3 bucket to be used.

    To enter the password, click the [...] button next to the password field, enter the password in double quotes in the pop-up dialog box, and click OK to save the settings.

Note that the format of the S3 file is S3N (S3 Native Filesystem).

Since a Hive table created in S3 is actually an external table, this Use S3 endpoint check box must be used with the Create an external table case being selected.

Advanced settings

Like table

Select this check box and enter the name of the Hive table you want to copy. This allows you to copy the definition of an existing table without copying its data.

For further information about the Like parameter, see Apache's information about Hive's Data Definition Language.

Create an external table

Select this check box to make the table to be created an external Hive table. This kind of Hive table leaves the raw data where it is if the data is in HDFS.

An external table is usually the better choice for accessing shared data existing in a file system.

For further information about an external Hive table, see Apache's documentation about Hive.

Table comment

Enter the description you want to use for the table to be created.

As select

Select this check box and enter the As select statement for creating a Hive table that is based on a Select statement.

Set clustered_by or skewed_by statement

Enter the Clustered by statement to cluster the data of a table or a partition into buckets, or/and enter the Skewed by statement to allow Hive to extract the heavily skewed data and put it into separate files. This is typically used for obtaining better performance during queries.

SerDe properties

If you are using the SerDe row format, you can add any custom SerDe properties to override the default ones used by the Hadoop engine of Talend Studio.

Table properties

Add any custom Hive table properties you want to override the default ones used by the Hadoop engine of Talend Studio.

Temporary path

If you do not want to set the Jobtracker and the NameNode when you execute the query select * from your_table_name, you need to set this temporary path. For example, /C:/select_all in Windows.

Hadoop properties

Talend Studio uses a default configuration for its engine to perform operations in a Hadoop distribution. If you need to use a custom configuration in a specific situation, complete this table with the property or properties to be customized. Then at runtime, the customized property or properties will override those default ones.

  • Note that if you are using the centrally stored metadata from the Repository, this table automatically inherits the properties defined in that metadata and becomes uneditable unless you change the Property type from Repository to Built-in.

For further information about the properties required by Hadoop and its related systems such as HDFS and Hive, see the documentation of the Hadoop distribution you are using or see Apache's Hadoop documentation and then select the version of the documentation you want. For demonstration purposes, the links to some properties are listed below:

Hive properties

Talend Studio uses a default configuration for its engine to perform operations in a Hive database. If you need to use a custom configuration in a specific situation, complete this table with the property or properties to be customized. Then at runtime, the customized property or properties will override those default ones. For further information, see Hive dedicated properties.
  • If you need to use Tez to run your Hive Job, add hive.execution.engine to the Properties column and Tez to the Value column, enclosing both of these strings in double quotation marks.

  • Note that if you are using the centrally stored metadata from the Repository, this table automatically inherits the properties defined in that metadata and becomes uneditable unless you change the Property type from Repository to Built-in.

Mapred job map memory mb and Mapred job reduce memory mb

You can tune the map and reduce computations by selecting the Set memory check box to set proper memory allocations for the computations to be performed by the Hadoop system.

In that situation, you need to enter the values you need in the Mapred job map memory mb and the Mapred job reduce memory mb fields, respectively. By default, the values are both 1000 which are normally appropriate for running the computations.

The memory parameters to be set are Map (in Mb), Reduce (in Mb) and ApplicationMaster (in Mb). These fields allow you to dynamically allocate memory to the map and the reduce computations and the ApplicationMaster of YARN.

Path separator in server

Leave the default value of the Path separator in server as it is, unless you have changed the separator used by your Hadoop distribution's host machine for its PATH variable or in other words, that separator is not a colon (:). In that situation, you must change this value to the one you are using in that host.

Set application name

Select this check box to avoid duplicates when you run your query on MapReduce or on Tez.

On MapReduce, the mapred.job.name is modified, and on Tez the hive.query.name is modified. Both names are modified with a concatenation of the project name, the Job name, the version of the Job, the date and the time.

tStatCatcher Statistics

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

Global Variables

Global Variables

QUERY: the query statement being processed. This is a Flow 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 more information about variables, see Using contexts and variables.

Usage

Usage rule

This component works standalone.

If Talend Studio used to connect to a Hive database is operated on Windows, you must manually create a folder called tmp in the root of the disk where Talend Studio is installed.

Row format

Set Delimited row format

 

Set SerDe row format

 

Die on error

Dynamic settings

Click the [+] button to add a row in the table and fill the Code field with a context variable to choose your database connection dynamically from multiple connections planned in your Job. This feature is useful when you need to access database tables having the same data structure but in different databases, 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 Dynamic schema and Creating a context group and define context variables in it.

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 Talend 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.

    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 Talend 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 Talend 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.

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