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Parquet Reader
StreamableKNIME BigData File Format Extension version 4.1.0.v201911281459 by KNIME AG, Zurich, Switzerland
Reader for Parquet files. It reads either single files or all files in a given directory.
Options
- Input
- The file or directory to read.
Input Type Mapping
Change the Parquet to KNIME type mapping configuration for subsequent nodes by selecting a KNIME type to the given Parquet Type. The dialog allows you to add new or change existing type mapping rules.
- Mapping by Name
- Columns that match the given name (or regular expression) and Parquet type will be mapped to the specified KNIME type.
- Mapping by Type
- Columns that match the given Parquet type will be mapped to the specified KNIME type.
Input Ports
Output Ports
Best Friends (Incoming)
- Amazon S3 Connection (43 %)
- Parquet Writer (21 %) Streamable
- Table Row To Variable Loop Start (14 %)
- String Manipulation (Variable) (7 %)
- HDFS Connection (7 %)
- Spark to Parquet (7 %)
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Best Friends (Outgoing)
- Row Filter (25 %) Streamable
- Column Filter (13 %) Streamable
- Parquet Writer (13 %) Streamable
- GroupBy (8 %)
- R View (Table) (8 %)
- String to Date&Time (8 %) Streamable
- Double To Int (4 %) Streamable
- Joiner (4 %)
- Sorter (4 %)
- String Manipulation (4 %) Streamable
- CASE Switch Data (End) (4 %)
- Table Difference Checker (4 %)
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Workflows
01_Flight_Delay_Statistics_Impala (KNIME Hub) - kn_example_python_read_parquet_file (KNIME Hub)
- kn_example_r_read_parquet_file (KNIME Hub)
- kn_example_r_read_single_csv_file (KNIME Hub)
- kn_example_r_read_single_xlsx_file (KNIME Hub)
- m_001_import_hive_parquet (KNIME Hub)
- m_020_build_model (KNIME Hub)
- m_050_make_new_prediction (KNIME Hub)
- m_120_build_model_one_year (KNIME Hub)
- s_401_spark_label_encoder (KNIME Hub)
- s_405_spark_prepare_data (KNIME Hub)
- s_410_h2o_automl_classification_python (KNIME Hub)
- s_415_h2o_automl_classification_r (KNIME Hub)
- s_420_spark_h2o_apply (KNIME Hub)
- s_430_spark_h2o_apply_normalized (KNIME Hub)
- Show all 15 workflows
Developers
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