tMysqlInput properties for Apache Spark Batch
These properties are used to configure tMysqlInput running in the Spark Batch Job framework.
The Spark Batch tMysqlInput component belongs to the Databases family.
This component also allows you to connect and read data from a RDS Aurora or a RDS MySQL database.
The component in this framework is available in all Talend products with Big Data and Talend Data Fabric.
Basic settings
Property type |
Either Built-In or Repository. Built-In: No property data stored centrally. Repository: Select the repository file where the properties are stored. |
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. |
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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. |
DB version |
Select the version of the database to be used. When the database to be used is RDS Aurora, you need to select Mysql 5. |
Host |
Database server IP address. |
Port |
Listening port number of DB server. |
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. When you create a Spark Job, avoid the reserved word line when naming the fields. |
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Built-In: You create and store the schema locally for this component only. |
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Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. |
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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Table Name |
Type in the name of the table from which you need to read data. This field is only available when you select Table from the Read from drop-down list. |
Read from |
Select the type of the source of the
data to be read.
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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. You can use pushdown predicate in the query to filter the data from the
database. Spark supports the following operators:
These fields are only available when you select Query from the Read from drop-down list. |
Advanced settings
Additional JDBC parameters |
Specify additional connection properties for the database connection you are creating. The properties are separated by semicolon and each property is a key-value pair, for example, encryption=1;clientname=Talend. This field is not available if the Use an existing connection check box is selected. |
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. Information noteNote:
Clear Trim all the String/Char columns to enable Trim columns in this field. |
Enable partitioning |
Select this check box to read data in partitions. Define, in double quotation marks, the following parameters to configure the
partitioning:
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 tMysqlConfiguration component present in the same Job to connect to MySQL. You need to select the Use an existing connection check box and then select the tMysqlConfiguration 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 |
In the Spark
Configuration tab in the Run
view, 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:
This connection is effective on a per-Job basis. |