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FTP Import Integration CL...
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FTP Import Integration CLI

You can also use the FTP 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 TD Toolbelt.

$ td --version
0.11.10

Create Seed Config File (seed.yml)

First, prepare seed.yml as shown in the following example, with your FTP details. You must also specify bucket name, and target file name (or prefix for multiple files).

in:
  type: ftp
  host: ftp.example.net
  port: 21
  user: anonymous
  password: XXXX
  path_prefix: /ftp/file/path/prefix # path of the *.csv or *.tsv file on your FTP server
out:
  mode: append

The Data Connector for FTP 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).

Active Mode is NOT supported.

If you’re using FTPS, specify additional details as follows:

in:
  type: ftp
  host: ftp.example.net
  port: 21
  user: anonymous
  password: "mypassword"
  path_prefix: /ftp/file/path/prefix
  ssl: true
  ssl_verify: false
out:
  mode: append

For more details, see modes for out plugin.

Guess Fields (Generate load.yml)

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

The guess command needs more than 3 rows and 2 columns in source data file, because the command assesses the column definition using sample rows from source data.

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

If you open load.yml, you’ll see the assessed file format definitions including file formats, encodings, column names, and types.

in:
  type: ftp
  host: ftp.example.net
  port: 21
  user: anonymous
  password: XXXX
  path_prefix: /ftp/file/path/prefix
  parser:
    charset: UTF-8
    newline: CRLF
    type: csv
    delimiter: ','
    quote: '"'
    escape: ''
    skip_header_lines: 1
    columns:
    - name: id
      type: long
    - name: company
      type: string
    - name: customer
      type: string
    - name: created_at
      type: timestamp
      format: '%Y-%m-%d %H:%M:%S'
out:
  mode: append

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

$ td connector:preview load.yml

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 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

Finally, 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 (see data partitioning) 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

At present, 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 FTP file import. We take great care in distributing and operating our scheduler to achieve high availability. By using this feature, you no longer need a cron daemon on your local data center.

For the scheduled import, the Data Connector for FTP 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, the connector 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 option, because Treasure Data’s storage is partitioned by time (see data partitioning).

$ 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, schedule is setup in UTC timezone. You can set the schedule in a timezone using -t or --timezone option. Note that --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

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
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