[V3] Table to Storage configuration file
This is the description of the JSON configuration file of a Table to Storage data operation.
The configuration file is in JSON format. It contains the following sections:
Global parameters: General information about the data operation. You can specify here default values for parameters that will apply to all the tasks, if the parameter is not overriden in the task description.
Table copy parameters: Optionally, you can add a creation step for a table that will contain the result of the extraction.
👁️🗨️ Example
Here is an example of TTS configuration file:
🌐 Global parameters
General information about the data operation.
You can specify here default values for parameters that will apply to all the tasks, if the parameter is not overriden in the task description.
Parameter | Description |
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$schema type: string optional | The url of the json-schema that contains the properties that your configuration must verify. Most Code Editor can use that to validate your configuration, display help boxes and enlighten issues. |
configuration_type type: string mandatory | Type of data operation. For a TTS data operation, the value is always "table-to-storage". |
configuration_id type: string mandatory | ID of the data operation. You can pick any name you want, but is has to be unique for this data operation type. Note that in case of conflict, the newly deployed data operation will overwrite the previous one. To guarantee its uniqueness, the best practice is to name your data operation by concatenating:
|
short_description type: string optional | Short description of the table to storage data operation. |
environment type: string mandatory | Deployment context. Values: PROD, PREPROD, STAGING, DEV. |
account type: string mandatory | Your account ID is a 6-digit number assigned to you by your Tailer Platform administrator. |
version type: string mandatory, otherwise default is 1 and in that case refers to the deprecated V1. | Version of the configuration. Must be "3" in order to use the latest features. Default : "1" for backward compatibility purposes but only version "3" supports the latest features. Version 1 is deprecated. |
activated type: boolean optional | Flag used to enable/disable the execution of the data operation. Default value: true |
archived type: boolean optional | Flag used to enable/disable the visibility of the data operation's configuration and runs in Tailer¯Studio. Default value: false |
doc_md type: string optional | Path to a file containing a detailed description of the data operation. The file must be in Markdown format. |
start_date type: string optional | Start date of the data operation. The format must be: "YYYY, MM, DD" Where:
|
schedule_interval type: string optional | A Tables to Tables data operation can be launched in two different ways:
Example For the data operation to start everyday at 7:00, you need to set it as follows:
You can find online tools to help you edit your Cron expression (for example, crontab.guru). |
print_header type: boolean optional | Print a header row in the exported data. Default value: true |
destination_format type: string optional | Define the format of the output file : Possible values: "NEWLINE_DELIMITED_JSON" (JSON file), "AVRO", "PARQUET" Note that if you specify "NEWLINE_DELIMITED_JSON", the field-delimiter parameter is not taken into account. Default value: "CSV" |
gcs_dest_bucket type: string mandatory | Google Cloud Storage destination bucket. This is the bucket where the data is going to be extracted. |
gcs_dest_prefix type: string mandatory | Path in the GCS bucket where the files will be extracted, e.g. "some/sub/dir". Note that you can use {{FD_DATE}} inside the path to include the current ISO date. e.g. "some/sub/dir/{{FD_DATE}}" |
gcp_project_id type: string mandatory | ID of the Google Cloud project containing the BigQuery instance. |
field_delimiter type: string optional | Separator for fields in the CSV output file, e.g. ";". Note: For Tab separator, set to "\t". Default value: " |
compression type: string optional | Compression mode for the output file. Possible values: "None", "GZIP", "SNAPPY". Note that if you specify "GZIP", a ".gz" extension will be added at the end of the filename. Default value: "None" |
sql_query_template type: string optional | If you want to use variables in your SQL query or script, you need to set this parameter to "TEMPLATE_CURRENT_DATE" (only supported value). This variable will be set to the execution date of the data operation (and not today's date). For example, if you want to retrieve data corresponding to the execution date, you can use the following instruction:
|
bq_data_location type: string optional | Bigquery location used by default in all tasks. If not specified the value 'EU' will be set. The list of available values can be found here : https://cloud.google.com/bigquery/docs/locations |
generate_top_file type: boolean optional | If true, generates an empty file when the data export is complete. This file name is defined by the file name template. For exemple if the file name template is "{{FD_DATE}}-my_data_extraction.csv" then the top file generated on 2022-01-01 will be named as: 20220101-my_data_extraction.csv.top Default value: false |
delete_dest_bucket_content type: boolean optional | If set to true, this parameter will trigger the preliminary deletion of any items present in the destination directory. This can prevent an issue when a new run of the same operation is needed after a fix. If the first run had generated file-0.csv and file-1.csv, and then the 2nd run only returns and erases file-0.csv, then you need to delete the destination bucket at the begining of the 2nd run, or you will end up with a file-0.csv from the 2nd run and a file-1.csv from the first run. Default value: false |
tasks type: array of maps mandatory | List of tasks the data operations will execute. Check the section below for detailed information on their parameters. |
📩Tasks Parametrers
With le latest version, it is now possible to export the data to different locations in one configuration. And this is possible thanks to the parameter "tasks".
Every task specifies an export. The tasks will use the parameters defined in the global configuration by default. If a parameter is specified in a task and in the global parameters, then the parameter in the task will overwrite the default parameter.
Parameter | Description |
---|---|
task_id type: string mandatory | The unique ID of your task. |
sql_file type: string mandatory | Path to the file containing the extraction query. |
output_filename type: string mandatory | Template for the output filename. You can use the following placeholders inside the name:
|
copy_table type: boolean optional | Parameter used to enable a copy of the output data in a BigQuery table. Default value: false |
dest_gcp_project_id mandatory if copy_table is set to "true" | ID of the GCP project that will contain the table copy. |
dest_gbq_dataset mandatory if copy_table is set to "true" | Name of the BigQuery dataset that will contain the table copy. |
dest_gbq_table_suffix optional, to use only if copy_table is set to "true" | The only supported value for this parameter is "dag_execution_date". This will add "_yyyymmdd" at the end of the table name to enable ingestion time partitioning. Default value: None |
bq_data_location type: string optional | Bigquery location used in this specific task. If not specified the value used will be the global "bq_data_location" set at the configuration root. The list of available values can be found here : https://cloud.google.com/bigquery/docs/locations |
and all the global parameters can be overwritten here | If a parameter is specified in a task and in the global parameters, then the parameter in the task will overwrite the default parameter. |
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