--- layout: doc_page title: "Druid Parquet Extension" --- # Druid Parquet Extension This module extends [Druid Hadoop based indexing](../../ingestion/hadoop.html) to ingest data directly from offline Apache Parquet files. Note: `druid-parquet-extensions` depends on the `druid-avro-extensions` module, so be sure to [include both](../../operations/including-extensions.html). ## Parquet Hadoop Parser This extension provides two ways to parse Parquet files: * `parquet` - using a simple conversion contained within this extension * `parquet-avro` - conversion to avro records with the `parquet-avro` library and using the `druid-avro-extensions` module to parse the avro data Selection of conversion method is controlled by parser type, and the correct hadoop input format must also be set in the `ioConfig`, `org.apache.druid.data.input.parquet.DruidParquetInputFormat` for `parquet` and `org.apache.druid.data.input.parquet.DruidParquetAvroInputFormat` for `parquet-avro`. Both parse options support auto field discovery and flattening if provided with a [flattenSpec](../../ingestion/flatten-json.html) with `parquet` or `avro` as the `format`. Parquet nested list and map [logical types](https://github.com/apache/parquet-format/blob/master/LogicalTypes.md) _should_ operate correctly with json path expressions for all supported types. `parquet-avro` sets a hadoop job property `parquet.avro.add-list-element-records` to `false` (which normally defaults to `true`), in order to 'unwrap' primitive list elements into multi-value dimensions. The `parquet` parser supports `int96` Parquet values, while `parquet-avro` does not. There may also be some subtle differences in the behavior of json path expression evaluation of `flattenSpec`. We suggest using `parquet` over `parquet-avro` to allow ingesting data beyond the schema constraints of Avro conversion. However, `parquet-avro` was the original basis for this extension, and as such it is a bit more mature. |Field | Type | Description | Required| |----------|-------------|----------------------------------------------------------------------------------------|---------| | type | String | Choose `parquet` or `parquet-avro` to determine how Parquet files are parsed | yes | | parseSpec | JSON Object | Specifies the timestamp and dimensions of the data, and optionally, a flatten spec. Valid parseSpec formats are `timeAndDims`, `parquet`, `avro` (if used with avro conversion). | yes | | binaryAsString | Boolean | Specifies if the bytes parquet column which is not logically marked as a string or enum type should be converted to strings anyway. | no(default == false) | When the time dimension is a [DateType column](https://github.com/apache/parquet-format/blob/master/LogicalTypes.md), a format should not be supplied. When the format is UTF8 (String), either `auto` or a explicitly defined [format](http://www.joda.org/joda-time/apidocs/org/joda/time/format/DateTimeFormat.html) is required. ### Examples #### `parquet` parser, `parquet` parseSpec ```json { "type": "index_hadoop", "spec": { "ioConfig": { "type": "hadoop", "inputSpec": { "type": "static", "inputFormat": "org.apache.druid.data.input.parquet.DruidParquetInputFormat", "paths": "path/to/file.parquet" }, ... }, "dataSchema": { "dataSource": "example", "parser": { "type": "parquet", "parseSpec": { "format": "parquet", "flattenSpec": { "useFieldDiscovery": true, "fields": [ { "type": "path", "name": "nestedDim", "expr": "$.nestedData.dim1" }, { "type": "path", "name": "listDimFirstItem", "expr": "$.listDim[1]" } ] }, "timestampSpec": { "column": "timestamp", "format": "auto" }, "dimensionsSpec": { "dimensions": [], "dimensionExclusions": [], "spatialDimensions": [] } } }, ... }, "tuningConfig": } } } ``` #### `parquet` parser, `timeAndDims` parseSpec ```json { "type": "index_hadoop", "spec": { "ioConfig": { "type": "hadoop", "inputSpec": { "type": "static", "inputFormat": "org.apache.druid.data.input.parquet.DruidParquetInputFormat", "paths": "path/to/file.parquet" }, ... }, "dataSchema": { "dataSource": "example", "parser": { "type": "parquet", "parseSpec": { "format": "timeAndDims", "timestampSpec": { "column": "timestamp", "format": "auto" }, "dimensionsSpec": { "dimensions": [ "dim1", "dim2", "dim3", "listDim" ], "dimensionExclusions": [], "spatialDimensions": [] } } }, ... }, "tuningConfig": } } ``` #### `parquet-avro` parser, `avro` parseSpec ```json { "type": "index_hadoop", "spec": { "ioConfig": { "type": "hadoop", "inputSpec": { "type": "static", "inputFormat": "org.apache.druid.data.input.parquet.DruidParquetAvroInputFormat", "paths": "path/to/file.parquet" }, ... }, "dataSchema": { "dataSource": "example", "parser": { "type": "parquet-avro", "parseSpec": { "format": "avro", "flattenSpec": { "useFieldDiscovery": true, "fields": [ { "type": "path", "name": "nestedDim", "expr": "$.nestedData.dim1" }, { "type": "path", "name": "listDimFirstItem", "expr": "$.listDim[1]" } ] }, "timestampSpec": { "column": "timestamp", "format": "auto" }, "dimensionsSpec": { "dimensions": [], "dimensionExclusions": [], "spatialDimensions": [] } } }, ... }, "tuningConfig": } } } ``` For additional details see [hadoop ingestion](../../ingestion/hadoop.html) and [general ingestion spec](../../ingestion/ingestion-spec.html) documentation.