tDeltaLakeInput properties for Apache Spark Batch

Define the source of the dataset

Select the source of the dataset you want to use between the following options:

Metastore: Retrieves data in table format from a metastore.

Files: Retrieves data in delta format from files.

Define a storage configuration component

Select the configuration component to be used to provide the configuration information for the connection to the target file system such as HDFS.

If you leave this check box clear, the target file system is the local system.

The configuration component to be used must be present in the same Job. For example, if you have dropped a tHDFSConfiguration component in the Job, you can select it to write the result in a given HDFS system.

This field is available only when you select Files from the Define the source of the dataset drop-down list in the Basic settings view.

Property type

Either Built-In or Repository.

Built-In: No property data stored centrally.

Repository: Select the repository file where the properties are stored.

The properties are stored centrally under the Hadoop Cluster node of the Repository tree.

The fields that come after are pre-filled in using the fetched data.

For further information about the Hadoop Cluster node, see the Getting Started Guide.

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.

Spark automatically infers data types for the columns in a PARQUET schema. In a Talend Job for Apache Spark, the Date type is inferred and stored as int96.

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.

Database

Enter, in double quotation marks, the name of the Delta Lake database to be used.

This field is available only when you select Metastore from the Define the source of the dataset drop-down list in the Basic settings view.

Table

Enter, in double quotation marks, the name of the table to be used.

This field is available only when you select Metastore from the Define the source of the dataset drop-down list in the Basic settings view.

Folder/File

Browse to, or enter the path pointing to the data to be used in the file system.

If you want to specify more than one files or directories in this field, separate each path using a comma (,).

The button for browsing does not work with the Spark Local mode; if you are using the other Spark Yarn modes that the Studio supports with your distribution, ensure that you have correctly configured the connection in a configuration component in the same Job, such as tHDFSConfiguration. Use the configuration component depending on the filesystem to be used.

This field is available only when you select Files from the Define the source of the dataset drop-down list in the Basic settings view.

This field is available only when you select SQL Query from the Define the source of the dataset drop-down list in the Basic settings view.

Select this check box to read a given timestamp-defined snapshot of the datasets to be used.

The format used by Deltalake is yyyy-MM-dd HH:mm:ss.

Delta Lake systematically creates slight differences between the upload time of a file and the metadata timestamp of this file. Bear in mind these differences when you need to filter data.

Usage rule

This component is used as an end component and requires an input link.

This Delta Lake layer is built on top of your Data Lake system, thus to be connected as part of your Data Lake system using the configuration component corresponding to your Data Lake system, for example, tAzureFSCofiguration.

Spark Connection

This connection is effective on a per-Job basis.