Hive Loader (legacy)

This Node Is Deprecated — This node is kept for backwards-compatibility, but the usage in new workflows is no longer recommended. The documentation below might contain more information.

This node is part of the legacy database framework. For more information on how to migrate to the new database framework see the migration section of the database documentation.

This node loads a KNIME data table into Hive. Hive requires imported data to be present on the Hive server, therefore this node first copies the data onto the Hive server. You can use any of the protocols supported by the file handling nodes, e.g. SSH/SCP or FTP. The data is then loaded into a Hive table and the uploaded file is deleted.

Additionally the data can be partitioned by selecting one or more compatible columns (e.g. integer or string). The node relies on Hive's dynamic partitioning.

Options

Target folder
A folder on the server where the temporary copy of the data is copied. The Hive server user needs read access to this folder.
Table name
The name of the new table in the database.
Drop existing table
If this option is selected, an existing table will be dropped and re-created. Otherwise the table is loaded into the existing table. Note that the import may fail in this case if the table structure and partitioning information do not match.
Partition columns
Here you can select one or more columns that should be used for partitioning the data in the table. A partitioned table requires a two-step import via a temporary table and therefore is much slower than import into an unpartitioned table.
NULL values or empty strings in string partition columns are placed into a special partition and returned as __HIVE_DEFAULT_PARTITION__ instead of NULL.

Input Ports

Icon
A connection to the remote Hive server
Icon
The data table that should be loaded into Hive
Icon
A connection to a Hive database

Output Ports

Icon
A database connection with the imported table

Views

This node has no views

Workflows

Links

Developers

You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.