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Move data from a DT bucket into a BigQuery table.
Ensure your user has access to the bucket. |
Provide the DT bucket name to read from. |
Provide the path of the files to read. |
Each file is synchronized to a unique table. Use a view or aggregate select. |
Open Source | YES |
Age | March 15, 2018 (4 years, 9 months) |
Authors | kenjora@google.com |
Shedule Days | Configured by user. |
Shedule Hours | Configured by user. |
[
{
"dt": {
"auth": {
"field": {
"name": "auth_read",
"kind": "authentication",
"order": 0,
"default": "user",
"description": "Credentials used for reading data."
}
},
"from": {
"bucket": {
"field": {
"name": "bucket",
"kind": "string",
"order": 2,
"default": "",
"description": "Name of bucket where DT files are stored."
}
},
"paths": {
"field": {
"name": "paths",
"kind": "string_list",
"order": 3,
"default": [],
"description": "List of prefixes to pull specific DT files."
}
},
"days": {
"field": {
"name": "days",
"kind": "integer",
"order": 4,
"default": 2,
"description": "Number of days back to synchronize."
}
},
"hours": {
"field": {
"name": "hours",
"kind": "integer",
"order": 5,
"default": 0,
"description": "Number of hours back to synchronize."
}
}
},
"to": {
"auth": {
"field": {
"name": "auth_write",
"kind": "authentication",
"order": 1,
"default": "service",
"description": "Credentials used for writing data."
}
},
"dataset": {
"field": {
"name": "dataset",
"kind": "string",
"order": 6,
"default": "",
"description": "Existing dataset in BigQuery."
}
}
}
}
}
]
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