---
title: Parquet
weight: 9
type: docs
aliases:
  - /dev/table/connectors/formats/parquet.html
---
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# Parquet Format

{{< label "Format: Serialization Schema" >}}
{{< label "Format: Deserialization Schema" >}}

The [Apache Parquet](https://parquet.apache.org/) format allows to read and write Parquet data.

Dependencies
------------

{{< sql_download_table "parquet" >}}

How to create a table with Parquet format
----------------

Here is an example to create a table using Filesystem connector and Parquet format.

```sql
CREATE TABLE user_behavior (
  user_id BIGINT,
  item_id BIGINT,
  category_id BIGINT,
  behavior STRING,
  ts TIMESTAMP(3),
  dt STRING
) PARTITIONED BY (dt) WITH (
 'connector' = 'filesystem',
 'path' = '/tmp/user_behavior',
 'format' = 'parquet'
)
```

Format Options
----------------

<table class="table table-bordered">
    <thead>
      <tr>
        <th class="text-left" style="width: 25%">Option</th>
        <th class="text-center" style="width: 8%">Required</th>
        <th class="text-center" style="width: 7%">Default</th>
        <th class="text-center" style="width: 10%">Type</th>
        <th class="text-center" style="width: 50%">Description</th>
      </tr>
    </thead>
    <tbody>
    <tr>
      <td><h5>format</h5></td>
      <td>required</td>
      <td style="word-wrap: break-word;">(none)</td>
      <td>String</td>
      <td>Specify what format to use, here should be 'parquet'.</td>
    </tr>
    <tr>
      <td><h5>parquet.utc-timezone</h5></td>
      <td>optional</td>
      <td style="word-wrap: break-word;">false</td>
      <td>Boolean</td>
      <td>Use UTC timezone or local timezone to the conversion between epoch time and LocalDateTime. Hive 0.x/1.x/2.x use local timezone. But Hive 3.x use UTC timezone.</td>
    </tr>
    </tbody>
</table>

Parquet format also supports configuration from [ParquetOutputFormat](https://www.javadoc.io/doc/org.apache.parquet/parquet-hadoop/1.10.0/org/apache/parquet/hadoop/ParquetOutputFormat.html).
For example, you can configure `parquet.compression=GZIP` to enable gzip compression.

Data Type Mapping
----------------

Currently, Parquet format type mapping is compatible with Apache Hive, but different with Apache Spark:

- Timestamp: mapping timestamp type to int96 whatever the precision is.
- Decimal: mapping decimal type to fixed length byte array according to the precision.

The following table lists the type mapping from Flink type to Parquet type.

<table class="table table-bordered">
    <thead>
      <tr>
        <th class="text-left">Flink Data Type</th>
        <th class="text-center">Parquet type</th>
        <th class="text-center">Parquet logical type</th>
      </tr>
    </thead>
    <tbody>
    <tr>
      <td>CHAR / VARCHAR / STRING</td>
      <td>BINARY</td>
      <td>UTF8</td>
    </tr>
    <tr>
      <td>BOOLEAN</td>
      <td>BOOLEAN</td>
      <td></td>
    </tr>
    <tr>
      <td>BINARY / VARBINARY</td>
      <td>BINARY</td>
      <td></td>
    </tr>
    <tr>
      <td>DECIMAL</td>
      <td>FIXED_LEN_BYTE_ARRAY</td>
      <td>DECIMAL</td>
    </tr>
    <tr>
      <td>TINYINT</td>
      <td>INT32</td>
      <td>INT_8</td>
    </tr>
    <tr>
      <td>SMALLINT</td>
      <td>INT32</td>
      <td>INT_16</td>
    </tr>
    <tr>
      <td>INT</td>
      <td>INT32</td>
      <td></td>
    </tr>
    <tr>
      <td>BIGINT</td>
      <td>INT64</td>
      <td></td>
    </tr>
    <tr>
      <td>FLOAT</td>
      <td>FLOAT</td>
      <td></td>
    </tr>
    <tr>
      <td>DOUBLE</td>
      <td>DOUBLE</td>
      <td></td>
    </tr>
    <tr>
      <td>DATE</td>
      <td>INT32</td>
      <td>DATE</td>
    </tr>
    <tr>
      <td>TIME</td>
      <td>INT32</td>
      <td>TIME_MILLIS</td>
    </tr>
    <tr>
      <td>TIMESTAMP</td>
      <td>INT96</td>
      <td></td>
    </tr>
    <tr>
      <td>ARRAY</td>
      <td>-</td>
      <td>LIST</td>
    </tr>
    <tr>
      <td>MAP</td>
      <td>-</td>
      <td>MAP</td>
    </tr>
    <tr>
      <td>ROW</td>
      <td>-</td>
      <td>STRUCT</td>
    </tr>
    </tbody>
</table>
