School of Hive - with KNIME's local Big Data environment (SQL for Big Data)

School of Hive - with KNIME's local Big Data environment (SQL for Big Data)

Demonstrates a collection of Hive functions using KNIME's local Big Data environment including creating table structures from scratch and from an existing file and working with partitions.
Partitions are an essential organizing principle of Big Data systems. They will make is easier to store and handel big data tables.
All examples are fully functional. You could switch out the local big data environment for your own one (Cloudera e.g.).

This example focusses on Hive-SQL script in executors. Similar effects could be achieved by using KNIME's DB nodes.
https://hub.knime.com/mlauber71/spaces/Public/latest/_db_sql_bigdata_hive_spark_meta_collection#externalresources

External resources

• MEDIUM Blog: KNIME, Databases and SQL
• HUB: School of Hive - with KNIME's local Big Data environment (SQL for Big Data)
• (official) KNIME Big Data Extensions User Guide
• L4-BD Introduction to Big Data with KNIME Analytics Platform
• This workflow demonstrates several methods to import one or many CSV file into Hive
• Hive - LanguageManual UDF - Date Functions
• This workflow demonstrates several methods to import one or many CSV file into Hive
• A meta collection of KNIME and databases (SQL, Big Data/Hive/Impala and Spark/PySpark)
• MAX_ROW_SIZE Query Option
• Create HIVE table and show the way it was created and describe the structure
• add fields to Hive table
• KNIME and Hive - load multiple CSV files at once via external table
• Combine Big Data, Spark and H2O.ai Sparkling Water