tHiveRow Standard properties
These properties are used to configure tHiveRow running in the Standard Job framework.
The Standard tHiveRow component belongs to the Big Data and the Databases families.
The component in this framework is available in all Talend products.
Basic settings
- When you use this component with Qubole on AWS:
API Token Click the ... button next to the API Token field to enter the authentication token generated for the Qubole user account to be used. For further information about how to obtain this token, see Manage Qubole account from the Qubole documentation.
This token allows you to specify the user account you want to use to access Qubole. Your Job automatically uses the rights and permissions granted to this user account in Qubole.
Cluster label Select the Cluster label check box and enter the name of the Qubole cluster to be used. If leaving this check box clear, the default cluster is used.
If you need details about your default cluster, ask the administrator of your Qubole service. You can also read this article from the Qubole documentation to find more information about configuring a default Qubole cluster.
Change API endpoint Select the Change API endpoint check box and select the region to be used. If leaving this check box clear, the default region is used.
For further information about the Qubole Endpoints supported on QDS-on-AWS, see Supported Qubole Endpoints on Different Cloud Providers.
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When you use this component with Google Dataproc:
Project identifier
Enter the ID of your Google Cloud Platform project.
If you are not certain about your project ID, check it in the Manage Resources page of your Google Cloud Platform services.
Cluster identifier
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 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 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.
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When you use this component with HDInsight:
WebHCat configuration
Enter the address and the authentication information of the Microsoft HD Insight cluster to be used. For example, the address could be your_hdinsight_cluster_name.azurehdinsight.net and the authentication information is your Azure account name: ychen. The 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 the 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 the Studio should retry to get a status when there is no status response.
HDInsight configuration
Enter the address and the authentication information of the Microsoft HD Insight cluster to be used. For example, the address could be your_hdinsight_cluster_name.azurehdinsight.net and the authentication information is your Azure account name: ychen. The 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.
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.
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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 server
Select the Hive server through which you want the Job using this component to execute queries on Hive.
This Hive server list is available only when the Hadoop distribution to be used such as HortonWorks Data Platform V1.2.0 (Bimota) supports HiveServer2. It allows you to select HiveServer2 (Hive 2), the server that better support concurrent connections of multiple clients than HiveServer (Hive 1).
For further information about HiveServer2, see https://cwiki.apache.org/confluence/display/Hive/Setting+Up+HiveServer2.
Host
Database server IP address.
Port
Listening port number of DB server.
Database
Fill this field with the name of the database.
Information noteNote:This field is not available when you select Embedded from the Connection mode list.
Username and Password
DB user authentication data.
To enter the password, click the [...] button next to the password field, and then in the pop-up dialog box enter the password between double quotes 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.-
If this cluster is a MapR cluster of the version 5.0.0 or later, you can set the MapR ticket authentication configuration in addition or as an alternative by following the explanation in Connecting to a security-enabled MapR.
Keep in mind that this configuration generates a new MapR security ticket for the username defined in the Job in each execution. If you need to reuse an existing ticket issued for the same username, leave both the Force MapR ticket authentication check box and the Use Kerberos authentication check box clear, and then MapR should be able to automatically find that ticket on the fly.
The values of the following parameters can be found in the hive-site.xml file of the Hive system to be used.-
Hive principal uses the value of hive.metastore.kerberos.principal. This is the service principal of the Hive Metastore.
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HiveServer2 local user principal uses the value of hive.server2.authentication.kerberos.principal.
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HiveServer2 local user keytab uses the value of hive.server2.authentication.kerberos.keytab
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Metastore URL uses the value of javax.jdo.option.ConnectionURL. This is the JDBC connection string to the Hive Metastore.
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Driver class uses the value of javax.jdo.option.ConnectionDriverName. This is the name of the driver for the JDBC connection.
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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.
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Password uses the value of javax.jdo.option.ConnectionPassword.
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.
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To enter the password, click the [...] button next to the password field, and then in the pop-up dialog box enter the password between double quotes 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 +
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Cloudera CDH4 +
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Pivotal HD 2.0 +
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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 ):-
Select the Set resourcemanager scheduler address check box and enter the Scheduler address in the field that appears.
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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.
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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.
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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.
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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.
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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 the Hadoop Map/Reduce framework, see the Map/Reduce tutorial in Apache's Hadoop documentation on http://hadoop.apache.org.
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 on http://hadoop.apache.org.
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.
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Property type |
Either Built-In or Repository. Built-In: No property data stored centrally. Repository: Select the repository file where the properties are stored. |
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, if you
need to share an existing connection between the two levels, for example, to share the
connection created by the parent Job with the child Job, you have to:
For an example about how to share a database connection across Job levels, see Talend Studio User Guide. |
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:
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Hive version |
Select the version of the Hadoop distribution you are using. The available options vary depending on the component you are using. |
Execution engine |
Select this check box and from the drop-down list, select the framework you need to use to run the Job. This list is available only when you are using the Embedded mode for the Hive connection and the distribution you are working
with is:
Before using Tez, ensure that the Hadoop cluster you are using supports Tez. You will need to configure the access to the relevant Tez libraries via the Advanced settings view of this component. For further information about Hive on Tez, see Apache's related documentation in https://cwiki.apache.org/confluence/display/Hive/Hive+on+Tez. Some examples are presented there to show how Tez can be used to gain performance over MapReduce. |
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:
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Built-in: The schema is created and stored locally for this component only. Related topic: see Talend Studio User Guide. |
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Repository: The schema already exists and is stored in the Repository, hence can be reused. Related topic: see Talend Studio User Guide. |
Table Name |
Name of the table to be processed. |
Query type |
Either Built-in or Repository. |
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Built-in: Fill in manually the query statement or build it graphically using SQLBuilder |
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Repository: Select the relevant query stored in the Repository. The Query field gets accordingly filled in. |
Guess Query |
Click the Guess Query button to generate the query which corresponds to your table schema in the Query field. |
This query uses Parquet objects |
When available, select this check box to indicate that the table to be handled uses the PARQUET format and thus make the component to call the required jar file. 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 the Studio.
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Query |
Enter your DB query paying particularly attention to properly sequence the fields in order to match the schema definition. For further information about the Hive query language, see https://cwiki.apache.org/confluence/display/Hive/LanguageManual. Information noteNote: Compressed data in the form of Gzip or Bzip2 can be processed through the query
statements. For details, see https://cwiki.apache.org/confluence/display/Hive/CompressedStorage.
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. |
Die on error |
This check box is selected by default. Clear the check box to skip the row on error and complete the process for error-free rows. If needed, you can retrieve the rows on error via a Row > Rejects link. |
Store by HBase |
Select this check box to display the parameters to be set to allow the Hive components to
access HBase tables:
For further information about this access involving Hive and HBase, see Apache's Hive documentation about Hive/HBase integration. |
Zookeeper quorum |
Type in the name or the URL of the Zookeeper service you use to coordinate the transaction between your Studio and your database. Note that when you configure the Zookeeper, you might need to explicitly set the zookeeper.znode.parent property to define the path to the root znode that contains all the znodes created and used by your database; then select the Set Zookeeper znode parent check box to define this property. |
Zookeeper client port |
Type in the number of the client listening port of the Zookeeper service you are using. |
Define the jars to register for HBase |
Select this check box to display the Register jar for HBase table, in which you can register any missing jar file required by HBase, for example, the Hive Storage Handler, by default, registered along with your Hive installation. |
Register jar for HBase |
Click the [+] button to add rows to this table, then, in the Jar name column, select the jar file(s) to be registered and in the Jar path column, enter the path(s) pointing to that or those jar file(s). |
Advanced settings
Tez lib |
Select how the Tez libraries are accessed:
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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. |
Propagate QUERY's recordset |
Select this check box to insert the result of the query into a COLUMN of the current flow. Select this column from the use column list. Information noteNote:
This option allows the component to have a different schema from that of the preceding component. Moreover, the column that holds the QUERY's recordset should be set to the type of Object and this component is usually followed by tParseRecordSet. |
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.
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 on http://hadoop.apache.org/docs and then select the version of the documentation you want. For demonstration purposes, the links to some properties are listed below:
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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 for Hive dedicated properties, see https://cwiki.apache.org/confluence/display/Hive/AdminManual+Configuration.
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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. |
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. |
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 further information about variables, see Talend Studio User Guide. |
Usage
Usage rule |
This component offers the benefit of flexible DB queries and covers all possible Hive QL queries.
tHiveRow can capture
the Application_ID values and write them in the Job logs once you have
activated Log4j and set the Log4j output level to Info for your Job involving tHiveRow.
If the 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 this Studio is installed. |
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 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.
For further information about how to install a Hadoop distribution, see the manuals corresponding to the Hadoop distribution you are using. |