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Following is a simple example showing how BigQuery Source would work.
A dataset already exist in Google BigQuery:121
project Id: vernal-seasdf-123456
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| name | count |
|---|---|
| Emma | 100 |
| Oscar | 334 |
| Peter | 223 |
| Jay | 1123 |
| Nicolas | 764 |
User pull the schema of the dataset:
| Inputs | Value |
|---|---|
| project Id | vernal-seasdf-123456 |
| dataset name | baby_names |
output schema:
| Schema | Type | Required | Description | |
|---|---|---|---|---|
| name | String | Yes | names of baby born in 2014 | |
| count | Integer | Yes | the number of occurrences of the name |
User run query agains dataset in BigQuery and pull the records:
| Inputs | Value |
|---|---|
| project Id | vernal-seasdf-123456 |
| query | SELECT name, count FROM baby_names ORDER BY count DESC LIMIT 3 |
output:
| name | count |
|---|---|
| Jay | 1123 |
| Nicolas | 764 |
| Oscar | 334 |
Design
CDAP provides two type of operations on the dataset stored in BigQuery: Query and Poll Results.
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