import-csv-files-serverless.md

title	Import CSV Files from Cloud Storage into {{{ .starter }}} or Essential
summary	Learn how to import CSV files from Amazon S3, GCS, Azure Blob Storage, or Alibaba Cloud Object Storage Service (OSS) into {{{ .starter }}} or {{{ .essential }}}.

Import CSV Files from Cloud Storage into {{{ .starter }}} or Essential

This document describes how to import CSV files from Amazon Simple Storage Service (Amazon S3), Google Cloud Storage (GCS), Azure Blob Storage, or Alibaba Cloud Object Storage Service (OSS) into {{{ .starter }}} or {{{ .essential }}}.

Note:

For TiDB Cloud Dedicated, see Import CSV Files from Cloud Storage into TiDB Cloud Dedicated.

Limitations

• To ensure data consistency, TiDB Cloud allows importing CSV files into empty tables only. To import data into an existing table that already contains data, you can import the data into a temporary empty table by following this document, and then use the INSERT SELECT statement to copy the data to the target existing table.

Step 1. Prepare the CSV files

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

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

2. Name the CSV files as follows:

   • If a CSV file contains all data of an entire table, name the file in the ${db_name}.${table_name}.csv 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 CSV files, append a numeric suffix to these CSV files. For example, ${db_name}.${table_name}.000001.csv and ${db_name}.${table_name}.000002.csv. 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.
   • TiDB Cloud supports importing compressed files in the following formats: .gzip, .gz, .zstd, .zst and .snappy. If you want to import compressed CSV files, name the files in the ${db_name}.${table_name}.${suffix}.csv.${compress} format, in which ${suffix} is optional and can be any integer such as '000001'. For example, if you want to import the trips.000001.csv.gz file to the bikeshare.trips table, you need to rename the file as bikeshare.trips.000001.csv.gz.

   Note:

   • To achieve better performance, it is recommended to limit the size of each compressed file to 100 MiB.
   • The Snappy compressed file must be in the official Snappy format. Other variants of Snappy compression are not supported.
   • For uncompressed files, if you cannot update the CSV filenames according to the preceding rules in some cases (for example, the CSV file links are also used by your other programs), you can keep the filenames unchanged and use the Mapping Settings in Step 4 to import your source data to a single target table.

Step 2. Create the target table schemas

Because CSV files do not contain schema information, before importing data from CSV 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, GCS, Azure Blob Storage, or Alibaba Cloud Object Storage Service directory where the CSV 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 CSV 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, GCS, Azure Blob Storage, or Alibaba Cloud Object Storage Service directory where the CSV 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 );

     Note:

     Each ${db_name}.${table_name}-schema.sql file should only contain a single DDL statement. If the file contains multiple DDL statements, only the first one takes effect.

Step 3. Configure cross-account access

To allow TiDB Cloud to access the CSV files in the Amazon S3, GCS, Azure Blob Storage, or Alibaba Cloud Object Storage Service bucket, do one of the following:

• If your CSV files are located in Amazon S3, configure Amazon S3 access for your cluster.

  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 CSV files are located in GCS, configure GCS access for your cluster.

• If your CSV files are located in Azure Blob Storage, configure Azure Blob Storage access for your cluster.

• If your CSV files are located in Alibaba Cloud Object Storage Service (OSS), configure Alibaba Cloud Object Storage Service (OSS) access for your cluster.

Step 4. Import CSV files

To import the CSV files to {{{ .starter }}} or {{{ .essential }}}, 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.

      Tip:

      You can use the combo box in the upper-left corner to switch between organizations, projects, and clusters.

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

2. Click Import data from Cloud Storage.

3. On the Import Data from Cloud Storage page, provide the following information:

   • Storage Provider: select Amazon S3.
   • Source Files URI:
     • When importing one file, enter the source file URI in the following format s3://[bucket_name]/[data_source_folder]/[file_name].csv. For example, s3://sampledata/ingest/TableName.01.csv.
     • When importing multiple files, enter the source folder URI in the following format s3://[bucket_name]/[data_source_folder]/. For example, s3://sampledata/ingest/.
   • Credential: you can use either an AWS Role ARN or an AWS access key to access your bucket. For more information, see Configure Amazon S3 access.
     • AWS Role ARN: enter the AWS Role ARN value.
     • AWS Access Key: enter the AWS access key ID and AWS secret access key.

4. Click Next.

5. In the Destination Mapping section, specify how source files are mapped to target tables.

   When a directory is specified in Source Files URI, the Use File naming conventions for automatic mapping option is selected by default.

   Note:

   When a single file is specified in Source Files URI, the Use File naming conventions for automatic mapping option is not displayed, and TiDB Cloud automatically populates the Source field with the file name. In this case, you only need to select the target database and table for data import.

   • To let TiDB Cloud automatically map all source files that follow the File naming conventions to their corresponding tables, keep this option selected and select CSV as the data format.

   • To manually configure the mapping rules to associate your source CSV files with the target database and table, unselect this option, and then fill in the following fields:

     • Source: enter the file name pattern in the [file_name].csv format. For example: TableName.01.csv. You can also use wildcards to match multiple files. Only * and ? wildcards are supported.

       • my-data?.csv: matches all CSV files that start with my-data followed by a single character, such as my-data1.csv and my-data2.csv.
       • my-data*.csv: matches all CSV files that start with my-data, such as my-data-2023.csv and my-data-final.csv.

     • Target Database and Target Table: select the target database and table to import the data to.

6. Click Next. TiDB Cloud scans the source files accordingly.

7. Review the scan results, check the data files found and corresponding target tables, and then click Start Import.

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

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.

      Tip:

      You can use the combo box in the upper-left corner to switch between organizations, projects, and clusters.

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

2. Click Import data from Cloud Storage.

3. On the Import Data from Cloud Storage page, provide the following information:

   • Storage Provider: select Google Cloud Storage.
   • Source Files URI:
     • When importing one file, enter the source file URI in the following format [gcs|gs]://[bucket_name]/[data_source_folder]/[file_name].csv. For example, [gcs|gs]://sampledata/ingest/TableName.01.csv.
     • When importing multiple files, enter the source folder URI in the following format [gcs|gs]://[bucket_name]/[data_source_folder]/. For example, [gcs|gs]://sampledata/ingest/.
   • Credential: you can use a GCS IAM Role Service Account key to access your bucket. For more information, see Configure GCS access.

4. Click Next.

5. In the Destination Mapping section, specify how source files are mapped to target tables.

   When a directory is specified in Source Files URI, the Use File naming conventions for automatic mapping option is selected by default.

   Note:

   When a single file is specified in Source Files URI, the Use File naming conventions for automatic mapping option is not displayed, and TiDB Cloud automatically populates the Source field with the file name. In this case, you only need to select the target database and table for data import.

   • To let TiDB Cloud automatically map all source files that follow the File naming conventions to their corresponding tables, keep this option selected and select CSV as the data format.

   • To manually configure the mapping rules to associate your source CSV files with the target database and table, unselect this option, and then fill in the following fields:

     • Source: enter the file name pattern in the [file_name].csv format. For example: TableName.01.csv. You can also use wildcards to match multiple files. Only * and ? wildcards are supported.

       • my-data?.csv: matches all CSV files that start with my-data followed by a single character, such as my-data1.csv and my-data2.csv.
       • my-data*.csv: matches all CSV files that start with my-data, such as my-data-2023.csv and my-data-final.csv.

     • Target Database and Target Table: select the target database and table to import the data to.

6. Click Next. TiDB Cloud scans the source files accordingly.

7. Review the scan results, check the data files found and corresponding target tables, and then click Start Import.

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

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.

      Tip:

      You can use the combo box in the upper-left corner to switch between organizations, projects, and clusters.

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

2. Click Import data from Cloud Storage.

3. On the Import Data from Cloud Storage page, provide the following information:

   • Storage Provider: select Azure Blob Storage.
   • Source Files URI:
     • When importing one file, enter the source file URI in the following format [azure|https]://[bucket_name]/[data_source_folder]/[file_name].csv. For example, [azure|https]://sampledata/ingest/TableName.01.csv.
     • When importing multiple files, enter the source folder URI in the following format [azure|https]://[bucket_name]/[data_source_folder]/. For example, [azure|https]://sampledata/ingest/.
   • Credential: you can use a shared access signature (SAS) token to access your bucket. For more information, see Configure Azure Blob Storage access.

4. Click Next.

5. In the Destination Mapping section, specify how source files are mapped to target tables.

   When a directory is specified in Source Files URI, the Use File naming conventions for automatic mapping option is selected by default.

   Note:

   When a single file is specified in Source Files URI, the Use File naming conventions for automatic mapping option is not displayed, and TiDB Cloud automatically populates the Source field with the file name. In this case, you only need to select the target database and table for data import.

   • To let TiDB Cloud automatically map all source files that follow the File naming conventions to their corresponding tables, keep this option selected and select CSV as the data format.

   • To manually configure the mapping rules to associate your source CSV files with the target database and table, unselect this option, and then fill in the following fields:

     • Source: enter the file name pattern in the [file_name].csv format. For example: TableName.01.csv. You can also use wildcards to match multiple files. Only * and ? wildcards are supported.

       • my-data?.csv: matches all CSV files that start with my-data followed by a single character, such as my-data1.csv and my-data2.csv.
       • my-data*.csv: matches all CSV files that start with my-data, such as my-data-2023.csv and my-data-final.csv.

     • Target Database and Target Table: select the target database and table to import the data to.

6. Click Next. TiDB Cloud scans the source files accordingly.

7. Review the scan results, check the data files found and corresponding target tables, and then click Start Import.

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

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.

      Tip:

      You can use the combo box in the upper-left corner to switch between organizations, projects, and clusters.

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

2. Click Import data from Cloud Storage.

3. On the Import Data from Cloud Storage page, provide the following information:

   • Storage Provider: select Alibaba Cloud OSS.
   • Source Files URI:
     • When importing one file, enter the source file URI in the following format oss://[bucket_name]/[data_source_folder]/[file_name].csv. For example, oss://sampledata/ingest/TableName.01.csv.
     • When importing multiple files, enter the source folder URI in the following format oss://[bucket_name]/[data_source_folder]/. For example, oss://sampledata/ingest/.
   • Credential: you can use an AccessKey pair to access your bucket. For more information, see Configure Alibaba Cloud Object Storage Service (OSS) access.

4. Click Next.

5. In the Destination Mapping section, specify how source files are mapped to target tables.

   When a directory is specified in Source Files URI, the Use File naming conventions for automatic mapping option is selected by default.

   Note:

   When a single file is specified in Source Files URI, the Use File naming conventions for automatic mapping option is not displayed, and TiDB Cloud automatically populates the Source field with the file name. In this case, you only need to select the target database and table for data import.

   • To let TiDB Cloud automatically map all source files that follow the File naming conventions to their corresponding tables, keep this option selected and select CSV as the data format.

   • To manually configure the mapping rules to associate your source CSV files with the target database and table, unselect this option, and then fill in the following fields:

     • Source: enter the file name pattern in the [file_name].csv format. For example: TableName.01.csv. You can also use wildcards to match multiple files. Only * and ? wildcards are supported.

       • my-data?.csv: matches all CSV files that start with my-data followed by a single character, such as my-data1.csv and my-data2.csv.
       • my-data*.csv: matches all CSV files that start with my-data, such as my-data-2023.csv and my-data-final.csv.

     • Target Database and Target Table: select the target database and table to import the data to.

6. Click Next. TiDB Cloud scans the source files accordingly.

7. Review the scan results, check the data files found and corresponding target tables, and then click Start Import.

8. 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 CSV files.
4. Try the import task again.

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.