Paginate a BigQuery result set

If you are trying to retrieve the results of a query to a BigQuery dataset that is larger than the Workflows memory limit, you can use a page token to paginate through the results. The page token represents the position in the result set, and is returned when additional results are available. This allows you to loop through a page of results at a time.

BigQuery hosts a number of public datasets that are available to the general public to query. In the following example, you query the USA Name Data public dataset to determine the most common names in the US between 1910 and 2013.

YAML

main:
  params: [input]
  steps:
    - init:
        assign:
          - pageToken: null
    - startQuery:
        call: googleapis.bigquery.v2.jobs.insert
        args:
          projectId: ${sys.get_env("GOOGLE_CLOUD_PROJECT_ID")}
          body:
            configuration:
              query:
                useLegacySql: false
                # Remove LIMIT from the query to iterate through all results
                query: SELECT name, SUM(number) AS total FROM `bigquery-public-data.usa_names.usa_1910_2013` GROUP BY name ORDER BY total DESC LIMIT 50
        result: query
    - getPage:
        call: googleapis.bigquery.v2.jobs.getQueryResults
        args:
          projectId: ${sys.get_env("GOOGLE_CLOUD_PROJECT_ID")}
          jobId: ${query.jobReference.jobId}
          maxResults: 10
          pageToken: ${pageToken}
        result: page
    - processPage:
        for:
          value: row
          in: ${page.rows}
          steps:
            - processRow:
                call: sys.log
                args:
                  data: ${row}
    - checkIfDone:
        switch:
          - condition: ${"pageToken" in page and page.pageToken != ""}
            assign:
              - pageToken: ${page.pageToken}
            next: getPage

JSON

{
  "main": {
    "params": [
      "input"
    ],
    "steps": [
      {
        "init": {
          "assign": [
            {
              "pageToken": null
            }
          ]
        }
      },
      {
        "startQuery": {
          "call": "googleapis.bigquery.v2.jobs.insert",
          "args": {
            "projectId": "${sys.get_env(\"GOOGLE_CLOUD_PROJECT_ID\")}",
            "body": {
              "configuration": {
                "query": {
                  "useLegacySql": false,
                  "query": "SELECT name, SUM(number) AS total FROM `bigquery-public-data.usa_names.usa_1910_2013` GROUP BY name ORDER BY total DESC LIMIT 50"
                }
              }
            }
          },
          "result": "query"
        }
      },
      {
        "getPage": {
          "call": "googleapis.bigquery.v2.jobs.getQueryResults",
          "args": {
            "projectId": "${sys.get_env(\"GOOGLE_CLOUD_PROJECT_ID\")}",
            "jobId": "${query.jobReference.jobId}",
            "maxResults": 10,
            "pageToken": "${pageToken}"
          },
          "result": "page"
        }
      },
      {
        "processPage": {
          "for": {
            "value": "row",
            "in": "${page.rows}",
            "steps": [
              {
                "processRow": {
                  "call": "sys.log",
                  "args": {
                    "data": "${row}"
                  }
                }
              }
            ]
          }
        }
      },
      {
        "checkIfDone": {
          "switch": [
            {
              "condition": "${\"pageToken\" in page and page.pageToken != \"\"}",
              "assign": [
                {
                  "pageToken": "${page.pageToken}"
                }
              ],
              "next": "getPage"
            }
          ]
        }
      }
    ]
  }
}

What's next