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Version: current [25.x]

Copying Data Into Apache Iceberg Tables

You can load data from CSV, JSON, and Parquet files into existing Iceberg tables. The copy operation loads data into columns in the target table that match corresponding columns represented in the data.

Performing analytics at scale on data that is in CSV or JSON files is not ideal. You can get much faster response times for your queries by querying data in Apache Iceberg tables, which use the column-oriented Parquet file format. This format is column-oriented, and supports efficient data storage and data retrieval at very high volumes and concurrencies. Even the performance of queries on Parquet files can be significantly improved upon by loading their data into Iceberg tables. When your data is in Iceberg tables, you can then make use of all of the features in Dremio's support of such tables.

The copy operation is supported on Iceberg tables in the following types of catalogs:

  • AWS Glue Data Catalog
  • Hive Metastore
  • Nessie Catalog

The storage location can be in the following types of object storage:

  • Azure Storage
  • Google Cloud Storage
  • HDFS
  • NAS
  • Amazon S3

The copy operation verifies that at least one column in the target table matches a column represented in the data files. It then follows these rules:

  • If a match is found, the values in the data files are loaded into the column or columns.
  • If additional non-matching columns are present in the data files, the values in these columns are not loaded.
  • If additional non-matching columns are present in the target table, the operation inserts NULL values into these columns.
  • If no column in the target table matches any column represented in the data files, the operation fails.

The copy operation ignores case when comparing column names.

To perform this operation, use the COPY INTO <table> SQL command.

New Parquet files that are added to an existing Iceberg table as a result of the copy operation are compressed according to the compression codec that is specified by the store.parquet.compression support key. If no value is explicitly set for the support key, Snappy compression is used by default. For information about this support key, see Parquet File Compression.

Routing to Specific Queues​

You can route jobs that run the COPY INTO <table> command to specific queues by using a routing rule that uses the query_label() condition. For more information, see Workload Management.

Requirements​

  • At least one column in the target table must match a column represented in every data file.
  • Do not duplicate column names in files. The operation throws an error if it finds duplicate names.
  • CSV data files must have a header line at the start of the file.

Type Coercion​

For a list of the type coercions used by the copy operation when copying data from CSV and JSON files, see Type Coercion When Copying Data from CSV or JSON Files Into Apache Iceberg Tables.

For the type coercions used by the copy operation when copying data from Parquet files, refer to this table: Supported and Unsupported Coercions for File-formatted Sources