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Import Apache Parquet Files from Amazon S3 or GCS into TiDB Cloud

You can import both uncompressed and Snappy compressed Apache Parquet format data files to TiDB Cloud. This document describes how to import Parquet files from Amazon Simple Storage Service (Amazon S3) or Google Cloud Storage (GCS) into TiDB Cloud.

Step 1. Prepare the Parquet files

  1. If a Parquet file is larger than 256 MB, consider splitting it into smaller files, each with a size around 256 MB.

    TiDB Cloud supports importing very large Parquet files but performs best with multiple input files around 256 MB in size. This is because TiDB Cloud can process multiple files in parallel, which can greatly improve the import speed.

  2. Name the Parquet files as follows:

    • If a Parquet file contains all data of an entire table, name the file in the ${db_name}.${table_name}.parquet format, which maps to the ${db_name}.${table_name} table when you import the data.
    • If the data of one table is separated into multiple Parquet files, append a numeric suffix to these Parquet files. For example, ${db_name}.${table_name}.000001.parquet and ${db_name}.${table_name}.000002.parquet. The numeric suffixes can be inconsecutive but must be in ascending order. You also need to add extra zeros before the number to ensure all the suffixes are in the same length.

Step 2. Create the target table schemas

Because Parquet files do not contain schema information, before importing data from Parquet files into TiDB Cloud, you need to create the table schemas using either of the following methods:

  • Method 1: In TiDB Cloud, create the target databases and tables for your source data.

  • Method 2: In the Amazon S3 or GCS directory where the Parquet files are located, create the target table schema files for your source data as follows:

    1. Create database schema files for your source data.

      If your Parquet files follow the naming rules in Step 1, the database schema files are optional for the data import. Otherwise, the database schema files are mandatory.

      Each database schema file must be in the ${db_name}-schema-create.sql format and contain a CREATE DATABASE DDL statement. With this file, TiDB Cloud will create the ${db_name} database to store your data when you import the data.

      For example, if you create a mydb-scehma-create.sql file that contains the following statement, TiDB Cloud will create the mydb database when you import the data.

      CREATE DATABASE mydb;
    2. Create table schema files for your source data.

      If you do not include the table schema files in the Amazon S3 or GCS directory where the Parquet files are located, TiDB Cloud will not create the corresponding tables for you when you import the data.

      Each table schema file must be in the ${db_name}.${table_name}-schema.sql format and contain a CREATE TABLE DDL statement. With this file, TiDB Cloud will create the ${db_table} table in the ${db_name} database when you import the data.

      For example, if you create a mydb.mytable-schema.sql file that contains the following statement, TiDB Cloud will create the mytable table in the mydb database when you import the data.

      CREATE TABLE mytable ( ID INT, REGION VARCHAR(20), COUNT INT );

Step 3. Configure cross-account access

To allow TiDB Cloud to access the Parquet files in the Amazon S3 or GCS bucket, do one of the following:

  • If your Parquet files are located in Amazon S3, configure Amazon S3 access.

    You can use either an AWS access key or a Role ARN to access your bucket. Once finished, make a note of the access key (including the access key ID and secret access key) or the Role ARN value as you will need it in Step 4.

  • If your Parquet files are located in GCS, configure GCS access.

Step 4. Import Parquet files to TiDB Cloud

To import the Parquet files to TiDB Cloud, take the following steps:

  1. Open the Import page for your target cluster.

    1. Log in to the TiDB Cloud console and navigate to the Clusters page of your project.

    2. Click the name of your target cluster to go to its overview page, and then click Import in the left navigation pane.

  2. On the Import page:

    • For a TiDB Dedicated cluster, click Import Data in the upper-right corner.
    • For a TiDB Serverless cluster, click the import data from S3 link above the upload area.
  3. Provide the following information for the source Parquet files:

    Depending on where you cluster is located, you can choose to import data from Amazon S3 or GCS.

    • Amazon S3
    • GCS
    • Location: select Amazon S3.
    • Data format: select Parquet.
    • Bucket URI: select the bucket URI where your Parquet files are located. Note that you must include / at the end of the URI, for example, s3://sampledate/ingest/.
    • Bucket Access (This field is visible only for AWS S3): you can use either an AWS access key or a Role ARN to access your bucket. For more information, see Configure Amazon S3 access.
      • AWS Access Keys: enter the AWS access key ID and AWS secret access key.
      • AWS Role ARN: enter the Role ARN value.
    • Location: use Google Cloud..
    • Data format: select Parquet.
    • Bucket gsutil URI: select the bucket URI where your Parquet files are located. Note that you must include / at the end of the URI, for example, gs://sampledate/ingest/.
    • Bucket Access: you can use a GCS IAM Role to access your bucket. For more information, see Configure GCS access.
  4. You can choose to import into pre-created tables, or import schema and data from the source.

    • Import into pre-created tables allows you to create tables in TiDB in advance and select the tables that you want to import data into. In this case, you can choose up to 1000 tables to import. You can click Chat2Query in the left navigation pane to create tables. For more information about how to use Chat2Query, see Explore Your Data with AI-Powered Chat2Query.
    • Import schema and data from S3 (This field is visible only for AWS S3) allows you to import SQL scripts for creating a table and import corresponding table data stored in S3 into TiDB.
    • Import schema and data from GCS (This field is visible only for GCS) allows you to import SQL scripts that create a table along with its corresponding data stored in GCS directly into TiDB.
  5. If the source files do not meet the naming conventions, you can specify a custom mapping rule between a single target table and the CSV file. After that, the data source files will be re-scanned using the provided custom mapping rule. To modify the mapping, click Advanced Settings and then click Mapping Settings. Note that Mapping Settings is available only when you choose to import into pre-created tables**.

    • Target Database: enter the name of the target database you select.

    • Target Tables: enter the name of the target table you select. Note that this field only accepts one specific table name, so wildcards are not supported.

    • Source file URIs and names: enter the source file URI and name in the following format s3://[bucket_name]/[data_source_folder]/[file_name].parquet. For example, s3://sampledate/ingest/TableName.01.parquet. You can also use wildcards to match the source files. For example:

      • s3://[bucket_name]/[data_source_folder]/my-data?.parquet: all Parquet files starting with my-data and one character (such as my-data1.parquet and my-data2.parquet) in that folder will be imported into the same target table.
      • s3://[bucket_name]/[data_source_folder]/my-data*.parquet: all Parquet files in the folder starting with my-data will be imported into the same target table.

      Note that only ? and * are supported.

  6. Click Start Import.

  7. When the import progress shows Completed, check the imported tables.

When you run an import task, if any unsupported or invalid conversions are detected, TiDB Cloud terminates the import job automatically and reports an importing error.

If you get an importing error, do the following:

  1. Drop the partially imported table.

  2. Check the table schema file. If there are any errors, correct the table schema file.

  3. Check the data types in the Parquet files.

    If the Parquet files contain any unsupported data types (for example, NEST STRUCT, ARRAY, or MAP), you need to regenerate the Parquet files using supported data types (for example, STRING).

  4. Try the import task again.

Supported data types

The following table lists the supported Parquet data types that can be imported to TiDB Cloud.

Parquet Primitive TypeParquet Logical TypeTypes in TiDB or MySQL
DOUBLEDOUBLEDOUBLE
FLOAT
FIXED_LEN_BYTE_ARRAY(9)DECIMAL(20,0)BIGINT UNSIGNED
FIXED_LEN_BYTE_ARRAY(N)DECIMAL(p,s)DECIMAL
NUMERIC
INT32DECIMAL(p,s)DECIMAL
NUMERIC
INT32N/AINT
MEDIUMINT
YEAR
INT64DECIMAL(p,s)DECIMAL
NUMERIC
INT64N/ABIGINT
INT UNSIGNED
MEDIUMINT UNSIGNED
INT64TIMESTAMP_MICROSDATETIME
TIMESTAMP
BYTE_ARRAYN/ABINARY
BIT
BLOB
CHAR
LINESTRING
LONGBLOB
MEDIUMBLOB
MULTILINESTRING
TINYBLOB
VARBINARY
BYTE_ARRAYSTRINGENUM
DATE
DECIMAL
GEOMETRY
GEOMETRYCOLLECTION
JSON
LONGTEXT
MEDIUMTEXT
MULTIPOINT
MULTIPOLYGON
NUMERIC
POINT
POLYGON
SET
TEXT
TIME
TINYTEXT
VARCHAR
SMALLINTN/AINT32
SMALLINT UNSIGNEDN/AINT32
TINYINTN/AINT32
TINYINT UNSIGNEDN/AINT32

Troubleshooting

Resolve warnings during data import

After clicking Start Import, if you see a warning message such as can't find the corresponding source files, resolve this by providing the correct source file, renaming the existing one according to Naming Conventions for Data Import, or using Advanced Settings to make changes.

After resolving these issues, you need to import the data again.

Zero rows in the imported tables

After the import progress shows Completed, check the imported tables. If the number of rows is zero, it means no data files matched the Bucket URI that you entered. In this case, resolve this issue by providing the correct source file, renaming the existing one according to Naming Conventions for Data Import, or using Advanced Settings to make changes. After that, import those tables again.

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