tTeradataInput

Executes a DB query with a strictly defined order which must correspond to the
schema definition.

tTeradataInput reads a database and
extracts fields based on a query. It passes on the field list to the next component via a
Main row link.

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 tTeradataInput Standard properties.

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

tTeradataInput Standard properties

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

The Standard
tTeradataInput component belongs to the Databases 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 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 click the relevant connection component to reuse the connection details you already defined. Note: 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: 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. 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 Talend Studio User Guide.
	Click this icon to open a database connection wizard and store the database connection parameters you set in the component Basic settings view. For more information about setting up and storing database connection parameters, see Talend Studio User Guide.
Host	Database server IP address
Database	Name of the database
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.
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. This component offers the advantage of the dynamic schema feature. This allows you to retrieve unknown columns from source files or to copy batches of columns from a source without mapping each column individually. For further information about dynamic schemas, see Talend Studio User Guide. This dynamic schema feature is designed for the purpose of retrieving unknown columns of a table and is recommended to be used for this purpose only; it is not recommended for the use of creating tables.
	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. 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.
Table name	Browse to, or enter the name of the table to be used.
Query type and Query	Enter your DB query paying particularly attention to properly sequence the fields in order to match the schema definition. If using the dynamic schema feature, the SELECT query must include the * wildcard, to retrieve all of the columns from the table selected.

Advanced settings

Additional JDBC parameters	Specify additional connection properties in the existing DB connection, to allow specific character set support. E.G.: CHARSET=KANJISJIS_OS to get support of Japanese characters.
Trim all the String/Char columns	Select this check box to remove leading and trailing whitespace from all the String/Char columns.
Trim column	Remove leading and trailing whitespace from defined columns.
Query band	Select this check box to use the Teradata Query Banding feature to add metadata to the query to be processed, such as the user running the query. This can help you, for example, identify the origin of this query. Once selecting the check box, the Query Band parameters table is displayed, in which you need to enter the metadata information to be added. This information takes the form of key/value pairs, for example, DpID in the Key column and Finance in the Value column. This check box actually generates the SET QUERY_BAND FOR SESSION statement with the key/value pairs declared in the Query Band parameters table. For further information about this statement, see http://www.info.teradata.com/HTMLPubs/DB_TTU_14_00/index.html#page/SQL_Reference/B035_1144_111A/End_Logging-Syntax.027.143.html. This check box is not available when you have selected the Using an existing connection check box. In this situation, if you need to use the Query Band feature, set it in the Advanced settings tab of the Teradata connection component to be used.
tStatCatcher Statistics	Select this check box to collect log data at the component level.

Global Variables

Global Variables	NB_LINE: the number of rows processed. This is an After variable and it returns an integer. 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.

NB_LINE: the number of rows processed. This is an After
variable and it returns an integer.

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 covers all possible SQL queries for Teradata databases.
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 Scenario: Reading data from databases through context-based dynamic connections and Scenario: 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.
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 covers all possible SQL queries for Teradata
databases.

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 Scenario: Reading data from databases through context-based dynamic connections and Scenario: 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.

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).

Related scenarios

For related scenarios, see:

tTeradataInput MapReduce properties

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

The MapReduce
tTeradataInput component belongs to the Databases 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 in which the properties are stored. The fields that follow are completed automatically using the data retrieved.
Host	Database server IP address
Database	Name of the database
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.
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. 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.
Table name	Browse to, or enter the name of the table to be used.
Query type and Query	Enter your DB query paying particularly attention to properly sequence the fields in order to match the schema definition.
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

Additional JDBC parameters	Specify additional connection properties in the existing DB connection, to allow specific character set support. E.G.: CHARSET=KANJISJIS_OS to get support of Japanese characters.
Trim all the String/Char columns	Select this check box to remove leading and trailing whitespace from all the String/Char columns.
Trim column	Remove leading and trailing whitespace from defined columns.

Usage

Usage rule	In a Talend Map/Reduce Job, it is used as a start component and requires a transformation component as output link. The 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. 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.
Hadoop Connection	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. This connection is effective on a per-Job basis.
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

In a
Talend
Map/Reduce Job, it is used as a start component and requires
a transformation component as output link. The 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.

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.

Hadoop Connection

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.

This connection is effective on a per-Job basis.

Limitation

Related scenarios

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

tTeradataInput properties for Apache Spark Batch

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

The Spark Batch
tTeradataInput component belongs to the Databases 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 in which the properties are stored. The fields that follow are completed automatically using the data retrieved.
Use an existing configuration	Select this check box and in the Component List click the relevant connection component to reuse the connection details you already defined.
	Click this icon to open a database connection wizard and store the database connection parameters you set in the component Basic settings view. For more information about setting up and storing database connection parameters, see Talend Studio User Guide.
Host	Database server IP address
Database	Name of the database
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.
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. 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.
Table Name	Type in the name of the table from which you need to read data.
Query type and Query	Specify the database query statement paying particularly attention to the properly sequence of the fields which must correspond to the schema definition. If you are using Spark V2.0 onwards, the Spark SQL does not recognize the prefix of a database table anymore. This means that you must enter only the table name without adding any prefix that indicates for example the schema this table belongs to. For example, if you need to perform a query in a table system.mytable, in which the system prefix indicates the schema that the mytable table belongs to, in the query, you must enter mytable only.

Advanced settings

Additional JDBC parameters	Specify additional connection properties in the existing DB connection, to allow specific character set support. E.G.: CHARSET=KANJISJIS_OS to get support of Japanese characters.
Spark SQL JDBC parameters	Add the JDBC properties supported by Spark SQL to this table. For a list of the user configurable properties, see JDBC to other database. This component automatically set the url, dbtable and driver properties by using the configuration from the Basic settings tab.
Trim all the String/Char columns	Select this check box to remove leading and trailing whitespace from all the String/Char columns.
Trim column	Remove leading and trailing whitespace from defined columns.
Enable partitioning	Select this check box to read data in partitions. Define, within double quotation marks, the following parameters to configure the partitioning: Partition column: the numeric column used as partition key. Lower bound of the partition stride and Upper bound of the partition stride: enter the upper bounds and the lower bound to determine the partition stride. These bounds do not filter the table rows. All rows in the table are partitioned and returned. Number of partitions: the number of partitions into which the table rows are split. Each Spark worker handles only one of the partitions at a time. The average size of the partitions is the result of the difference between the upper bound and the lower bound divided by the number of partitions, that is to say, (upperBound – lowerBound)/partitionNumber, while the first and the last partitions also include all the other rows that are not contained in the other partitions. For example, to partition 1000 rows into 4 partitions, if you enter 0 for the lower bound and 1000 for the upper bound, each partition will contain 250 rows and so the partitioning is even. If you enter 250 for the lower bound and 750 for the upper bound, the second and the third partition will each contain 125 rows and the first and the last partitions each 375 rows. With this configuration, the partitioning is skewed.

Usage

Usage rule	This component is used as a start component and requires an output link.. This component should use a tTeradataConfiguration component present in the same Job to connect to Oracle. You need to select the Use an existing configuration check box and then select the tTeradataConfiguration component to be used. 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.
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 used as a start component and requires an output link..

This component should use a tTeradataConfiguration
component present in the same Job to connect to Oracle. You need to select the Use an existing configuration check box and then select the tTeradataConfiguration component to be used.

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.

Limitation

Related scenarios

For a scenario about how to use the same type of component in a Spark Batch Job, see Writing and reading data from MongoDB using a Spark Batch Job.

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tTeradataInput – Docs for ESB 6.x

tTeradataInput

tTeradataInput Standard properties

Basic settings

Advanced settings

Global Variables

Usage

Related scenarios

tTeradataInput MapReduce properties

Basic settings

Advanced settings

Usage

Related scenarios

tTeradataInput properties for Apache Spark Batch

Basic settings

Advanced settings

Usage

Related scenarios

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