Data Export Overview

The data export feature writes query result sets or Apache Doris table data to a specified storage system in a specified file format. It is commonly used for result set downloads and cross-system data exchange.

Data Export vs. Data Backup

Both data export and data backup can output data from Apache Doris to external storage, but they target different scenarios. The following table compares the core differences between the two:

Comparison Dimension	Data Export	Data Backup
Final storage location	HDFS, object storage, local file system	HDFS, object storage
Data format	Open formats such as Parquet, ORC, CSV	Apache Doris internal storage format
Execution speed	Medium (requires reading data and converting to the target format)	Fast (uploads Doris data files directly, no parsing or conversion required)
Flexibility	Allows flexible export scope definition through SQL	Supports only table-level full backup
Typical use scenarios	Result set download, data exchange between different systems	Data backup, data migration between Apache Doris clusters

Choosing an Export Method

Apache Doris provides the following three data export methods, each suited to different export needs:

• SELECT INTO OUTFILE: supports exporting any SQL result set.
• EXPORT: supports exporting partial or full data at the table level.
• MySQL DUMP: data export compatible with MySQL Dump commands.

Capability Comparison of the Three Methods

The following table compares the three export methods across execution mode, SQL capabilities, concurrency, and supported formats, helping you choose quickly:

Comparison Dimension	SELECT INTO OUTFILE	EXPORT	MySQL DUMP
Synchronous / Asynchronous	Synchronous	Asynchronous (check progress with SHOW EXPORT after submission)	Synchronous
Supports arbitrary SQL	Supported	Not supported	Not supported
Export specified partitions	Supported	Supported	Not supported
Export specified tablets	Supported	Not supported	Not supported
Concurrent export	Supported, high concurrency (limited by single-node operators such as ORDER BY)	Supported, high concurrency (Tablet-level concurrency)	Not supported, single-threaded export
Supported export formats	Parquet, ORC, CSV	Parquet, ORC, CSV	MySQL Dump proprietary format
Supports external tables	Supported	Partially supported	Not supported
Supports views	Supported	Supported	Supported
Supported export locations	S3, HDFS	S3, HDFS	LOCAL

Applicable Scenarios

SELECT INTO OUTFILE

Suitable for the following scenarios:

• The exported data needs to go through complex computation logic, such as filtering, aggregation, or joins.
• Scenarios suitable for executing synchronous tasks.

For detailed usage, see SELECT INTO OUTFILE.

EXPORT

Suitable for the following scenarios:

• Single-table export of large data volumes that requires only simple filter conditions.
• Scenarios that require asynchronous task submission.

For detailed usage, see Export Asynchronous Export.

MySQL Dump

Suitable for the following scenarios:

• Compatibility with the MySQL ecosystem, with the need to export both table schemas and data.
• Used only for development, testing, or cases with very small data volumes.

For detailed usage, see MySQL Dump.

Column Type Mapping for Exported Files

The Parquet and ORC file formats have their own data type definitions, and Apache Doris automatically converts internal data types to the corresponding Parquet/ORC types during export. The CSV format has no type definitions; all data is output as text.

The mappings between Apache Doris data types and the ORC and Parquet formats are listed below.

ORC Type Mapping

Doris Type	ORC Type
boolean	boolean
tinyint	tinyint
smallint	smallint
int	int
bigint	bigint
largeInt	string
date	string
datev2	string
datetime	string
datetimev2	timestamp
float	float
double	double
char / varchar / string	string
decimal	decimal
struct	struct
map	map
array	array
json	string
variant	string
bitmap	binary
quantile_state	binary
hll	binary

Parquet Type Mapping

When Apache Doris exports to the Parquet file format, it first converts the in-memory Doris data to the Arrow in-memory format, and then Arrow writes it out to the Parquet file. The mappings are as follows:

Doris Type	Arrow Type	Parquet Physical Type	Parquet Logical Type
boolean	boolean	BOOLEAN
tinyint	int8	INT32	INT_8
smallint	int16	INT32	INT_16
int	int32	INT32	INT_32
bigint	int64	INT64	INT_64
largeInt	utf8	BYTE_ARRAY	UTF8
date	utf8	BYTE_ARRAY	UTF8
datev2	date32	INT32	DATE
datetime	utf8	BYTE_ARRAY	UTF8
datetimev2	timestamp	INT96 / INT64	TIMESTAMP(MICROS/MILLIS/SECONDS)
float	float32	FLOAT
double	float64	DOUBLE
char / varchar / string	utf8	BYTE_ARRAY	UTF8
decimal	decimal128	FIXED_LEN_BYTE_ARRAY	DECIMAL(scale, precision)
struct	struct		Parquet Group
map	map		Parquet Map
array	list		Parquet List
json	utf8	BYTE_ARRAY	UTF8
variant	utf8	BYTE_ARRAY	UTF8
bitmap	binary	BYTE_ARRAY
quantile_state	binary	BYTE_ARRAY
hll	binary	BYTE_ARRAY

note

In versions 2.1.11 and 3.0.7, the parquet.enable_int96_timestamps property is supported to specify whether the Doris datetimev2 type is stored as INT96 or INT64 in Parquet. The default is INT96. INT96 has been deprecated in the Parquet standard and is used only for compatibility with legacy systems (such as Hive versions before 4.0).

Related Documents

• Export Asynchronous Export: use the EXPORT command to asynchronously export table or partition data.
• SELECT INTO OUTFILE: use SELECT INTO OUTFILE to synchronously export query results.
• MySQL Dump: use the mysqldump tool to export table schemas and data.
• Data Export Best Practices: export concurrency tuning and methods for evaluating export speed.