Paging Through Query Results

This document describes how to page through query results using the BigQuery REST API.

Paging through results using the API

All collection.list methods return paginated results under certain circumstances. The number of results per page is controlled by the maxResults property.

Method	Pagination criteria	Default maxResults value	Maximum maxResults value
Tabledata.list	Returns paginated results if the response size is more than 10 MB of serialized JSON or more than maxResults rows.	100,000	100,000
All other collection.list methods	Returns paginated results if the response is more than maxResults rows.	50	1,000

If you set maxResults to a value greater than the maximum value listed above, the results are paginated based on the maximum value.

A page is a subset of the total number of rows. If your results are more than one page of data, the result data will have a pageToken property. To retrieve the next page of results, make another list call and include the token value as a URL parameter named pageToken.

The bigquery.tabledata.list method, which is used to page through table data, uses a row offset value or a page token. See Browsing table data for information.

The following samples demonstrate paging through bigquery results.

C#

Before trying this sample, follow the C# setup instructions in the BigQuery Quickstart Using Client Libraries . For more information, see the BigQuery C# API reference documentation .

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using Google.Api.Gax;
using Google.Apis.Bigquery.v2.Data;
using Google.Cloud.BigQuery.V2;
using System;
using System.Collections.Generic;
using System.Linq;

public class BigQueryBrowseTable
{
    public void BrowseTable(
        string projectId = "your-project-id"
    )
    {
        BigQueryClient client = BigQueryClient.Create(projectId);
        TableReference tableReference = new TableReference()
        {
            TableId = "shakespeare",
            DatasetId = "samples",
            ProjectId = "bigquery-public-data"
        };
        // Load all rows from a table
        PagedEnumerable<TableDataList, BigQueryRow> result = client.ListRows(
            tableReference: tableReference,
            schema: null
        );
        // Print the first 10 rows
        foreach (BigQueryRow row in result.Take(10))
        {
            Console.WriteLine($"{row["corpus"]}: {row["word_count"]}");
        }
    }
}

Java

Before trying this sample, follow the Java setup instructions in the BigQuery Quickstart Using Client Libraries . For more information, see the BigQuery Java API reference documentation .

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TableId tableIdObject = TableId.of(datasetName, tableName);
// This example reads the result 100 rows per RPC call. If there's no need to limit the number,
// simply omit the option.
TableResult tableData =
    bigquery.listTableData(tableIdObject, TableDataListOption.pageSize(100));
for (FieldValueList row : tableData.iterateAll()) {
  // do something with the row
}

Go

Before trying this sample, follow the Go setup instructions in the BigQuery Quickstart Using Client Libraries . For more information, see the BigQuery Go API reference documentation .

The Google Cloud Client Library for Go automatically paginates by default, so you do not need to implement pagination yourself, for example:

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table := client.Dataset(datasetID).Table(tableID)
it := table.Read(ctx)
for {
	var row []bigquery.Value
	err := it.Next(&row)
	if err == iterator.Done {
		break
	}
	if err != nil {
		return err
	}
	fmt.Println(row)
}

Node.js

Before trying this sample, follow the Node.js setup instructions in the BigQuery Quickstart Using Client Libraries . For more information, see the BigQuery Node.js API reference documentation .

The Google Cloud Client Library for Node.js automatically paginates by default, so you do not need to implement pagination yourself, for example:

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// Imports the Google Cloud client library
const BigQuery = require('@google-cloud/bigquery');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = "your-project-id";
// const datasetId = "my_dataset";
// const tableId = "my_table";

// Creates a client
const bigquery = new BigQuery({
  projectId: projectId,
});

// Lists rows in the table
bigquery
  .dataset(datasetId)
  .table(tableId)
  .getRows()
  .then(results => {
    const rows = results[0];
    console.log('Rows:');
    rows.forEach(row => console.log(row));
  })
  .catch(err => {
    console.error('ERROR:', err);
  });

PHP

Before trying this sample, follow the PHP setup instructions in the BigQuery Quickstart Using Client Libraries . For more information, see the BigQuery PHP API reference documentation .

Pagination happens automatically in the Google Cloud Client Library for PHP using the generator function rows, which fetches the next page of results during iteration.

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use Google\Cloud\BigQuery\BigQueryClient;

/** Uncomment and populate these variables in your code */
// $projectId = 'The Google project ID';
// $datasetId = 'The BigQuery dataset ID';
// $tableId   = 'The BigQuery table ID';
// $maxResults = 10;

$maxResults = 10;
$startIndex = 0;

$options = [
    'maxResults' => $maxResults,
    'startIndex' => $startIndex
];
$bigQuery = new BigQueryClient([
    'projectId' => $projectId,
]);
$dataset = $bigQuery->dataset($datasetId);
$table = $dataset->table($tableId);
$numRows = 0;
foreach ($table->rows($options) as $row) {
    print('---');
    foreach ($row as $column => $value) {
        printf('%s: %s' . PHP_EOL, $column, $value);
    }
    $numRows++;
}

Python

Before trying this sample, follow the Python setup instructions in the BigQuery Quickstart Using Client Libraries . For more information, see the BigQuery Python API reference documentation .

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# from google.cloud import bigquery
# client = bigquery.Client()

dataset_ref = client.dataset('samples', project='bigquery-public-data')
table_ref = dataset_ref.table('shakespeare')
table = client.get_table(table_ref)  # API call

# Load all rows from a table
rows = client.list_rows(table)
assert len(list(rows)) == table.num_rows

# Load the first 10 rows
rows = client.list_rows(table, max_results=10)
assert len(list(rows)) == 10

# Specify selected fields to limit the results to certain columns
fields = table.schema[:2]  # first two columns
rows = client.list_rows(table, selected_fields=fields, max_results=10)
assert len(rows.schema) == 2
assert len(list(rows)) == 10

# Use the start index to load an arbitrary portion of the table
rows = client.list_rows(table, start_index=10, max_results=10)

# Print row data in tabular format
format_string = '{!s:<16} ' * len(rows.schema)
field_names = [field.name for field in rows.schema]
print(format_string.format(*field_names))  # prints column headers
for row in rows:
    print(format_string.format(*row))      # prints row data

Ruby

Before trying this sample, follow the Ruby setup instructions in the BigQuery Quickstart Using Client Libraries . For more information, see the BigQuery Ruby API reference documentation .

Pagination happens automatically in the Google Cloud Client Library for Ruby using Table#data and Data#next.

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require "google/cloud/bigquery"

def browse_table
  bigquery = Google::Cloud::Bigquery.new project_id: "bigquery-public-data"
  dataset  = bigquery.dataset "samples"
  table    = dataset.table "shakespeare"

  # Load all rows from a table
  rows = table.data

  # Load the first 10 rows
  rows = table.data max: 10

  # Print row data
  rows.each { |row| puts row }
end

Requesting arbitrary pages and avoiding redundant list calls

When you page backwards or jump to arbitrary pages using cached pageToken values, it is possible that the data in your pages might have changed since it was last viewed but there is no clear indication that the data might have changed. To mitigate this, you can use the Etag property.

Every collection.list method (except for Tabledata) returns an Etag property in the result. This property is a hash of the page results that can be used to verify whether the page has changed since last request. When you make a request to BigQuery with an Etag value, BigQuery compares the Etag value to the ETag value returned by the API and responds based on whether the ETag values match. You can use ETags to help avoid redundant list calls in the following ways:

• If you only want to return list values if the values have changed:

  If you only want to return a page of list values if the values have changed, you can make a list call with a previously-stored ETag using the HTTP "if-none-match" header. If the ETag you provide doesn't match the ETag on the server, BigQuery returns a page of new list values. If the ETags do match, BigQuery returns a HTTP 304 "Not Modified" result and no values. An example of this might be a webpage where users might periodically fill in information that is stored in BigQuery. You can avoid making redundant list calls to BigQuery if there are no changes to your data by using the if-none-match header with ETags.

• If you only want to return list values if the values have not changed:

  If you only want to return a page of list values if the list values have not changed, you can use the HTTP "if-match" header. BigQuery matches the ETag values and returns the page of results if the results have not changed or returns a 412 "Precondition Failed" result if the page has changed.

Note: Although ETags are a great way to avoid making redundant list calls, you can apply the same methods to identifying if any objects have changed. For example, you can perform a Get request for a specific table and use ETags to determine if the table has changed before returning the full response.