Skip to main content
Pentaho Documentation

Table Input

Parent article

The Table Input step reads information from a connected database using SQL statements. Basic SQL statements can be generated automatically by clicking the Get SQL select statement button.

AEL considerations

When using the Table Input step with Adaptive Execution Layer, consider the following factors for Hive and Impala database connections, which can affect performance and results.

  • The following options in the step are not supported:
    • Enable Lazy conversion.
    • Execute for each row.
    • Pooling and Clustering database connection options.
  • Structures, arrays, and user-defined data types are not supported.
  • You can access Hive managed tables in ORC format using the Hive Warehouse Connector (HWC).

Connect to a Hive database

We support Hive version 2.x.y. To connect to a Hive database using AEL, Hive must be on the same cluster as Spark and managed by YARN.

You can use AEL with HWC to access Hive managed tables in ORC format. For details, see Configuring the AEL daemon for the Hive Warehouse Connector.

Connect to an Impala database

We support Impala versions 2.2.x. Before you can use the Table Input step to connect to an Impala database through AEL, you must download and install the Cloudera Impala driver.

Perform the following steps to download and install the Cloudera Impala driver:

Procedure

  1. Stop the AEL daemon.

  2. Go to https://www.cloudera.com/, select Downloads and click Impala JDBC Driver Downloads.

  3. Select Impala JDBC Connector 2.5.42 from the menu and follow the site's instructions for downloading.

    A ZIP file containing the Impala_jdbc_2.5.42 driver is downloaded.
  4. Unzip the impala_jdbc_2.5.42.zip file to a local folder.

    The contents of the ZIP file are extracted to the folder. The unpacked contents include a documentation folder and two ZIP files. You only need the ImpalaJDBC41-2.5.42.zip.
  5. Open the ClouderaImpalaJDBC-2.5.42 folder and unzip the ClouderaImpalaJDBC41_2.5.42.zip file to a local folder.

    The associated JAR files are extracted from the ZIP file.
  6. Copy all the JAR files, except log4j-1.2.14.jar, to the pentaho/design-tools/data-integration/adaptive-execution/extra folder.

    CautionThe log4j-1.2.14.jar file should not be copied as it is already present and will cause conflicts.
  7. Save and close the file.

    The Cloudera Impala driver is installed.
  8. Restart the AEL daemon.

Results

You can now use the Table Input step to connect to an Impala database through AEL

General

Table input step

The following fields are general to this transformation step:

FieldDescription
Step nameSpecify the unique name of the Table Input step on the canvas. You can customize the name or leave it as the default.
ConnectionUse the list to select the name of an existing database connection.

If you do not have an existing connection, click New or Wizard. If you need to modify an existing connection, click Edit. See Define Data Connections for instructions.

Note: When using an Impala database in AEL, select Cloudera Impala.

Note: When using HWC in AEL, select Hadoop Hive 2/3.

Options

The Table Input step has the following options:

OptionDescription
SQLSpecify a SQL statement to read information from the connected database. You can also click the Get SQL select statement button to browse tables and automatically generate a basic select statement.
Store column info in step metaSelect this option to use the cached metadata stored in the KTR without making a database connection to query the table.
NoteIf you are using Spark as your processing engine, select this option. (Required)
Enable lazy conversionSelect this option to enable the lazy conversion algorithm. When selected, lazy conversion avoids unnecessary data type conversions when possible, which can significantly improve performance.
Replace variables in script?Select this option to replace variables in the script. This feature provides testing capabilities with or without variable substitutions.
Insert data from stepSpecify the input step name where PDI can expect information to come from. This information can then be inserted into the SQL statement. The locator where PDI inserts information is indicated with a question mark: ?.
Execute for each row?Select this option to execute the query for each individual row.
Limit sizeSpecify the number of lines to read from the database. A value of zero (0) indicates to read all lines.
Preview (button)Click Preview to open a new window and view an execution log derived from a temporary transformation with two steps: the Table Input step and the Dummy step. To see the log, click Logs in the Preview window that opens.

Example

Below is an SQL statement:

SELECT * FROM customers WHERE changed_date BETWEEN ? AND ?

This SQL statement requests two calendar dates, to create a range, that are read from the Insert data from step option. The target date range can be provided using the Get System Info step. For example, if you want to read all customers that have had their data changed yesterday, you can get a target range for yesterday and read the customer data.

Metadata injection support

You can use the Metadata Injection supported fields with the ETL Metadata Injection step to pass metadata to your transformation at runtime. The following fields of the Table Input step support metadata injection:

  • Connection
  • SQL
  • Enable Lazy Conversion
  • Replace Variables in Script?
  • Insert Data from Step
  • Limit Size