White space in column name is not supported for Parquet files. Note currently Copy activity doesn't support LZO when read/write Parquet files. When writing Parquet files, all columns are automatically converted to be nullable for compatibility reasons. Spark SQL provides support for both reading and writing Parquet files that automatically preserves the schema of the original data. Supported types are " none", " gzip", " snappy" (default), and " lzo". Parquet is a columnar format that is supported by many other data processing systems. When reading from Parquet files, Data Factories automatically determine the compression codec based on the file metadata. The compression codec to use when writing to Parquet files. See details in connector article -> Dataset properties section. Each file-based connector has its own location type and supported properties under location. The type property of the dataset must be set to Parquet. Reading Parquet files The arrow::FileReader class reads data into Arrow Tables and Record Batches. The Parquet C++ implementation is part of the Apache Arrow project and benefits from tight integration with the Arrow C++ classes and facilities. The same principle applies for ORC, text file, and JSON storage formats. The Parquet format is a space-efficient columnar storage format for complex data. This section provides a list of properties supported by the Parquet dataset. For example, Athena can successfully read the data in a table that uses Parquet file format when some Parquet files are compressed with Snappy and other Parquet files are compressed with GZIP. Dataset propertiesįor a full list of sections and properties available for defining datasets, see the Datasets article. By default, the service uses min 64 MB and max 1G. This means that JVM will be started with Xms amount of memory and will be able to use a maximum of Xmx amount of memory. The flag Xms specifies the initial memory allocation pool for a Java Virtual Machine (JVM), while Xmx specifies the maximum memory allocation pool. If you copy data to/from Parquet format using Self-hosted Integration Runtime and hit error saying "An error occurred when invoking java, message: :Java heap space", you can add an environment variable _JAVA_OPTIONS in the machine that hosts the Self-hosted IR to adjust the min/max heap size for JVM to empower such copy, then rerun the pipeline.Įxample: set variable _JAVA_OPTIONS with value -Xms256m -Xmx16g.
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