SFTP Server Import Integration

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The Data Connector for SFTP enables you to import files stored on your SFTP server to Treasure Data.

For SFTP_V2 Server Import Integration, see SFTP_V2 Server Import Integration.

Prerequisites

• Basic knowledge of Treasure Data.

• Requires that your private key is in a version format earlier than OpenSSH 7.8. If you use OpenSSH 7.8 or later, use the '-m PEM' option to generate a private key.

• Before using this connector, determine valid protocols for your environment.

  • If you intend to use SFTP, you can use this integration for SFTP.
  • If you intend to use FTP or FTPS, try connecting with FTP Import Integration.
  • Check your accepted IP range and port if you are using a firewall. Sometimes, server administrators change the default port number from TCP 22 for security reasons.
  • “PuTTY” and other formats are not supported.

• After installation and configuration, review the Job logs for warnings and errors that can provide information about the success of your import.

Limitations

• Support only the STORED and DEFLATE compression methods.
• Multi-part gzip file may not work.
• The connection timeout setting doesn't function properly in v.1 so the import job could run for a long time instead of timing out.

Static IP Address of Treasure Data Integration

If your security policy requires IP whitelisting, you must add Treasure Data's IP addresses to your allowlist to ensure a successful connection.

Please find the complete list of static IP addresses, organized by region, at the following link:
https://api-docs.treasuredata.com/en/overview/ip-addresses-integrations-result-workers/

Import from SFTP server via TD Console

You can use TD Console to create your data connector.

Create a New Connection

When you configure a data connection, you need to provide authentication to access the integration. In Treasure Data, you can configure the authentication and then specify the source information.

1. Open TD Console.
2. Navigate to Integrations Hub > Catalog.
3. Search and select SFTP.

4. Select Create, and the following dialog opens.

5. Enter the required credentials for your remote SFTP instance.

• Host: The host information of the remote SFTP instance, for example, an IP address.
• Port: The connection port on the remote SFTP instance. The default port number is 22.
• User: The user name used to connect to the remote FTP instance.
• Authentication mode: The way you choose to authenticate with your SFTP server.
• Secret key file: Required if public / private key pair is selected as Authentication Mode. (DSA, RSA, and ECDSA are supported.)
• Passphrase for secret key file: (Optional) If required, provide a passphrase for the provided secret file.
• Retry limit: Number of times to retry a failed connection (default 10).
• Timeout: Connection timeout in seconds (default 600).

6. Select Continue. Provide a name for your connection.

7. If you would like to share this connection with other users in your organization, check the Share with others checkbox. If this box is unchecked, this connection is visible only to you.
8. Select Done.

Transfer Data into Treasure Data

To get the data from your SFTP server into Treasure Data, you can set up an ad hoc one-time or recurring transfer at a regular intervals. After creating the authenticated connection, you are automatically taken to Authentications.

1. Search for the connection you created.
2. Select New Source.

Create a Connection

3. Type a name for your Source in the Data Transfer field**.**

4. Click Next.

Identify a Source Table

1. The Source dialog opens.

2. Edit the following parameters.

Data Settings

1. Select Next. The Data Settings page opens.
2. (Optional) Edit the data settings.

Filters

Filters are available in the Create Source or Edit Source import settings for your S3, FTP, or SFTP connectors.

Import Integration Filters enable you to modify your imported data after you have completed Editing Data Settings for your import.

To apply import integration filters:

1. Select Next in Data Settings.The Filters dialog opens.
2. Select the filter option you want to add.
3. Select Add Filter. The parameter dialog for that filter opens.
4. Edit the parameters. For information on each filter type, see one of the following:

• Retaining Columns Filter
• Adding Columns Filter
• Dropping Columns Filter
• Expanding JSON Filter
• Digesting Filter

5. Optionally, to add another filter of the same type, select Add within the specific column filter dialog.
6. Optionally, to add another filter of a different type, select the filter option from the list and repeat the same steps.
7. After you have added the filters you want, select **Next.**The Data Preview dialog opens.

Data Preview

You can see a preview of your data before running the import by selecting Generate Preview. Data preview is optional and you can safely skip to the next page of the dialog if you choose to.

1. Select Next. The Data Preview page opens.
2. If you want to preview your data, select Generate Preview.
3. Verify the data.

Data Placement

For data placement, select the target database and table where you want your data placed and indicate how often the import should run.

1. Select Next. Under Storage, you will create a new or select an existing database and create a new or select an existing table for where you want to place the imported data.

2. Select a Database > Select an existing or Create New Database.

3. Optionally, type a database name.

4. Select a Table> Select an existing or Create New Table.

5. Optionally, type a table name.

6. Choose the method for importing the data.

   • Append (default)-Data import results are appended to the table. If the table does not exist, it will be created.
   • Always Replace-Replaces the entire content of an existing table with the result output of the query. If the table does not exist, a new table is created.
   • Replace on New Data-Only replace the entire content of an existing table with the result output when there is new data.

7. Select the Timestamp-based Partition Key column. If you want to set a different partition key seed than the default key, you can specify the long or timestamp column as the partitioning time. As a default time column, it uses upload_time with the add_time filter.

8. Select the Timezone for your data storage.

9. Under Schedule, you can choose when and how often you want to run this query.

Run once

1. Select Off.
2. Select Scheduling Timezone.
3. Select Create & Run Now.

Repeat Regularly

1. Select On.
2. Select the Schedule. The UI provides these four options: @hourly, @daily and @monthly or custom cron.
3. You can also select Delay Transfer and add a delay of execution time.
4. Select Scheduling Timezone.
5. Select Create & Run Now.

After your transfer has run, you can see the results of your transfer in Data Workbench > Databases.

Import from SFTP server via CLI (Toolbelt)

You can also use the SFTP data connector from the command line interface. The following instructions show you how to import data using the CLI.

Install ‘td’ command v0.11.9 or later

Install the most current Treasure Data Toolbelt.

$ td --version
0.11.10

Create Seed Config File (seed.yml)

Prepare seed.yml as shown in the following example, with your SFTP details. We support two authentication methods: Public / Private Key Pair, and Password.

Public and Private Key Pair Authentication

Create seed.yml with the following content.

in:
  type: sftp
  host: HOST
  port: <PORT, default is 22>
  user: USER
  secret_key_file:
 content: |
-----BEGIN RSA PRIVATE KEY-----
Proc-Type: 4,ENCRYPTED
DEK-Info: AES-128-CBC...
...
-----END RSA PRIVATE KEY-----
  secret_key_passphrase: PASSPHRASE
  user_directory_is_root: true
  timeout: 600
  path_prefix: /path/to/sample
out:
  mode: append
  exec: {}

secret_key_file requires OpenSSH format.

Password Authentication

Create seed.yml with the following content.

in:
  type: sftp
  host: HOST
  port: <PORT, default is 22>
  auth_method: password
  user: USER
  password: PASSWORD
  user_directory_is_root: true
  timeout: 600
  path_prefix: /path/to/sample
out:
  mode: append
  exec: {}

You can use the following special characters in the password: "#$!*@"

If you are using the proxy, add the additional information as shown:

in:
  type: sftp
  host: HOST
  port: <PORT, default is 22>
  ....
  proxy:
    type: http
    host: PROXY_HOST
    port: PROXY_PORT
    user: PROXY_USER
    password: PROXY_PASSWORD
    command: SOMETHING COMMAND IF NEEDED

The Data Connector for SFTP imports all files that match the specified prefix (e.g. path_prefix: path/to/sample_ –> path/to/sample_201501.csv.gz, path/to/sample_201502.csv.gz, …, path/to/sample_201505.csv.gz).

Guess Fields (Generate load.yml)

Use connector:guess. This command automatically reads the source file, and assesses (uses logic to guess) the file format.

$ td connector:guess seed.yml -o load.yml

If you open load.yml, you’ll see the guessed file format definitions including file formats, encodings, column names, and types. This example is trying to load CSV files.

in:
  type: sftp
  host: HOST
  port: <PORT, default is 22>
  user: USER
  secret_key_file:
 content: |
-----BEGIN RSA PRIVATE KEY-----
Proc-Type: 4,ENCRYPTED
DEK-Info: AES-128-CBC...
...
-----END RSA PRIVATE KEY-----
  secret_key_passphrase: PASSPHRASE
  user_directory_is_root: true
  timeout: 600
  path_prefix: /path/to/sample
  parser:
 skip_header_lines: 1
 charset: UTF-8
 newline: CRLF
 type: csv
 delimiter: ','
 quote: '"'
 columns:
 - {name: id, type: long}
 - {name: account, type: long}
 - {name: time, type: timestamp, format: "%Y-%m-%d %H:%M:%S"}
 - {name: purchase, type: timestamp, format: "%Y%m%d"}
 - {name: comment, type: string}
 - {name: json_column, type: json}
out:
  mode: append
  exec: {}

Then, you can preview how the system will parse the file by using the preview command.

$ td connector:preview load.yml
+-------+---------+----------+---------------------+
| id | company | customer | created_at |
+-------+---------+----------+---------------------+
| 11200 | AA Inc. | David | 2015-03-31 06:12:37 |
| 20313 | BB Imc. |Tom | 2015-04-01 01:00:07 |
| 32132 | CC Inc. | Fernando | 2015-04-01 10:33:41 |
| 40133 | DD Inc. | Cesar | 2015-04-02 05:12:32 |
| 93133 | EE Inc. |  Jake | 2015-04-02 14:11:13 |
+-------+---------+----------+---------------------+

The guess command needs over 3 rows and 2 columns in the source data file because it guesses column definition using sample rows from source data.

If the system detects your column name or column type unexpectedly, modify load.yml directly and preview again.

Currently, the Data Connector supports parsing of “boolean”, “long”, “double”, “string”, and “timestamp” types.

You also must create a local database and table prior to executing the data load job. Follow these steps:

$ td database:create td_sample_db
$ td table:create td_sample_db td_sample_table

Execute Load Job

Submit the load job. It may take a couple of hours depending on the size of the data. Specify the Treasure Data database and table where the data should be stored.

It’s also recommended to specify --time-column option, because Treasure Data’s storage is partitioned by time. If the option is not provided, the data connector chooses the first long or timestamp column as the partitioning time. The type of the column specified by --time-column must be either of long and timestamp type.

If your data doesn’t have a time column you can add a time column by using add_time filter option. For more details see add_time filter plugin.

$ td connector:issue load.yml --database td_sample_db --table td_sample_table --time-column created_at

The connector:issue command assumes that you have already created a *database(td_sample_db)*and a table(td_sample_table). If the database or the table do not exist in TD, the connector:issue command fails, so create the database and table manually or use --auto-create-table option with td connector:issue command to auto create the database and table:

$ td connector:issue load.yml --database td_sample_db --table td_sample_table --time-column created_at --auto-create-table

The Data Connector does not sort records on server-side. To use time-based partitioning effectively, sort records in files beforehand.

If you have a field called time, you don't have to specify the --time-column option.

$ td connector:issue load.yml --database td_sample_db --table td_sample_table

Scheduled Execution

You can schedule periodic Data Connector execution for incremental SFTP file import. We configure our scheduler carefully to ensure high availability. By using this feature, you no longer need a crondaemon on your local data center.

For the scheduled import, the Data Connector for SFTP imports all files that match with the specified prefix (e.g. path_prefix: path/to/sample_ –> path/to/sample_201501.csv.gz, path/to/sample_201502.csv.gz, …, path/to/sample_201505.csv.gz) at first and remembers the last path (path/to/sample_201505.csv.gz) for the next execution.

On the second and on subsequent runs, it imports only files that comes after the last path in alphabetical (lexicographic) order. (path/to/sample_201506.csv.gz, …)

Create the Schedule

A new schedule can be created using the td connector:create command. The following are required: the name of the schedule, the cron-style schedule, the database and table where the data will be stored, and the Data Connector configuration file.

$ td connector:create
 daily_import
 "10 0 * * *"
 td_sample_db
 td_sample_table
 load.yml

It’s also recommended to specify the --time-column opton because Treasure Data’s storage is partitioned by time.

$ td connector:create
 daily_import
 "10 0 * * *"
 td_sample_db
 td_sample_table
 load.yml
 --time-column created_at

The cron parameter also accepts three special options: @hourly, @daily and @monthly.

By default, the schedule is set up in UTC timezone. You can set the schedule in a timezone using -t or --timezone option. The --timezone option supports only extended timezone formats like 'Asia/Tokyo', 'America/Los_Angeles' etc. Timezone abbreviations like PST, CST are not supported and may lead to unexpected schedules.

List the Schedules

You can see the list of currently scheduled entries by running the command td connector:list.

$ td connector:list

Show the Setting and Schedule History

td connector:show shows the execution setting of a schedule entry.

$ td connector:show daily_import
Name  : daily_import
Cron  : 10 0 * * *
Timezone : UTC
Delay : 0
Database : td_sample_db
Table : td_sample_table
Config
---
in:
  type: sftp
  host: HOST
  port: <PORT, default is 22>
  auth_method: password
  user: USER
  password: PASSWORD
  path_prefix: /sftp/file/path/prefix
  parser:
 charset: UTF-8
 ...

td connector:history shows the execution history of a schedule entry. To investigate the results of each individual run, use td job jobid.

% td connector:history daily_import

Import from SFTP Server via Workflow

For sample workflows of importing files from your STFP server, view Treasure Boxes.