google-cloud-python: BigQuery: Error 413 (Request Entity Too Large)!!1

Python 3 google-cloud-bigquery==0.29.0

To reproduce: Function:

def get_result_dataframe(query):
    query_job = client.query(query)
    return query_job.to_dataframe()

Query: ‘SELECT * FROM project.dataset.table_with_lots_of_columns LIMIT 1000’ Result: Error 413 (Request Entity Too Large)!!1 More data from log: Seems like it queries the table first to get all the possible columns in the table and then makes an API call to the actual table with every column possible in the query’s select statement. The query size then becomes too large.

About this issue

Original URL
State: closed
Created 6 years ago
Comments: 24 (21 by maintainers)

Commits related to this issue

Update job.py fix for #4864 — committed to VikramTiwari/google-cloud-python by VikramTiwari 6 years ago
BigQuery: Don't use `selected_fields` for listing query result rows (#5072) * Update job.py fix for #4864 * Adds system tests for listing rows from table with many columns Order of rows in t... — committed to googleapis/google-cloud-python by VikramTiwari 6 years ago

Most upvoted comments

@shivafractal Rather than passing an 800,000 item list as a query parameter, I would consider uploading those values into a separate (maybe temporary?) table and then building the query by joining with it.

tseaver on Feb 4, 2019

Haven’t tested but let me know if that works. @tswast @bmabey

VikramTiwari on Mar 20, 2018

Yeah, 0.27 and before got query results using https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/getQueryResults, which is slower but also easier to get right in the client.

I’ll give the backend folks a little time to see if they can increase the request limit size. If not, we do have a workaround, which is to get the destination table object and then list rows (or we can pretend we have a full Table object by populating the reference and the schema).

tswast on Feb 22, 2018

Okay, I am able to reproduce if I pass the schema in as selected_fields, which is what query() does behind the scenes.

System test:

    def _create_table_many_columns(self, rows):
        # Load a table with many columns
        dataset = self.temp_dataset(_make_dataset_id('list_rows'))
        table_id = 'many_columns'
        table_ref = dataset.table(table_id)
        self.to_delete.insert(0, table_ref)
        schema = [
            bigquery.SchemaField(
                'column_{}_with_long_name'.format(col_i),
                'INTEGER')
            for col_i in range(len(rows[0]))]
        body = six.StringIO(
            '{}\n{}\n'.format(','.join(rows[0]), ','.join(rows[1])))
        config = bigquery.LoadJobConfig()
        config.schema = schema
        job = Config.CLIENT.load_table_from_file(
            body, table_ref, job_config=config)
        job.result()
        return table_ref, schema

    def test_list_rows_many_columns(self):
        rows = [[], []]
        for col_i in range(1000):
            rows[0].append(str(col_i))
            rows[1].append(str(10000 - col_i))
        table_ref, schema = self._create_table_many_columns(rows)

        rows = list(Config.CLIENT.list_rows(table_ref, selected_fields=schema))

        assert len(rows) == 2
        assert rows[0][437] == 437
        assert rows[1][9999] == 1

    def test_query_many_columns(self):
        rows = [[], []]
        for col_i in range(1000):
            rows[0].append(str(col_i))
            rows[1].append(str(10000 - col_i))
        table_ref, _ = self._create_table_many_columns(rows)

        rows = list(Config.CLIENT.query(
            'SELECT * FROM `{}.many_columns`'.format(table_ref.dataset_id)))

        assert len(rows) == 2
        assert rows[0][437] == 437
        assert rows[1][9999] == 1

With 10,000 columns, the request to list rows (tabledata) doesn’t even finish sending. The connection breaks before it can get sent.

requests.exceptions.ConnectionError: ('Connection aborted.', BrokenPipeError(32, 'Broken pipe'))


_________________________________________________________ TestBigQuery.test_query_many_columns __________________________________________________________
Traceback (most recent call last):
  File "/Users/swast/.pyenv/versions/3.6.2/envs/google-cloud-python/lib/python3.6/site-packages/urllib3/connectionpool.py", line 601, in urlopen
    chunked=chunked)
  File "/Users/swast/.pyenv/versions/3.6.2/envs/google-cloud-python/lib/python3.6/site-packages/urllib3/connectionpool.py", line 357, in _make_request
    conn.request(method, url, **httplib_request_kw)
  File "/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/http/client.py", line 1239, in request
    self._send_request(method, url, body, headers, encode_chunked)
  File "/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/http/client.py", line 1285, in _send_request
    self.endheaders(body, encode_chunked=encode_chunked)
  File "/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/http/client.py", line 1234, in endheaders
    self._send_output(message_body, encode_chunked=encode_chunked)
  File "/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/http/client.py", line 1026, in _send_output
    self.send(msg)
  File "/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/http/client.py", line 986, in send
    self.sock.sendall(data)
  File "/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/ssl.py", line 965, in sendall
    v = self.send(data[count:])
  File "/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/ssl.py", line 935, in send
    return self._sslobj.write(data)
  File "/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/ssl.py", line 636, in write
    return self._sslobj.write(data)
BrokenPipeError: [Errno 32] Broken pipe
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File “/Users/swast/.pyenv/versions/3.6.2/envs/google-cloud-python/lib/python3.6/site-packages/requests/adapters.py”, line 440, in send
timeout=timeout
File “/Users/swast/.pyenv/versions/3.6.2/envs/google-cloud-python/lib/python3.6/site-packages/urllib3/connectionpool.py”, line 639, in urlopen
_stacktrace=sys.exc_info()[2])
File “/Users/swast/.pyenv/versions/3.6.2/envs/google-cloud-python/lib/python3.6/site-packages/urllib3/util/retry.py”, line 357, in increment
raise six.reraise(type(error), error, _stacktrace)
File “/Users/swast/.pyenv/versions/3.6.2/envs/google-cloud-python/lib/python3.6/site-packages/urllib3/packages/six.py”, line 685, in reraise
raise value.with_traceback(tb)
File “/Users/swast/.pyenv/versions/3.6.2/envs/google-cloud-python/lib/python3.6/site-packages/urllib3/connectionpool.py”, line 601, in urlopen
chunked=chunked)
File “/Users/swast/.pyenv/versions/3.6.2/envs/google-cloud-python/lib/python3.6/site-packages/urllib3/connectionpool.py”, line 357, in _make_request
conn.request(method, url, **httplib_request_kw)
File “/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/http/client.py”, line 1239, in request
self._send_request(method, url, body, headers, encode_chunked)
File “/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/http/client.py”, line 1285, in _send_request
self.endheaders(body, encode_chunked=encode_chunked)
File “/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/http/client.py”, line 1234, in endheaders
self._send_output(message_body, encode_chunked=encode_chunked)
File “/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/http/client.py”, line 1026, in _send_output
self.send(msg)
File “/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/http/client.py”, line 986, in send
self.sock.sendall(data)
File “/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/ssl.py”, line 965, in sendall
v = self.send(data[count:])
File “/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/ssl.py”, line 935, in send
return self._sslobj.write(data)
File “/Users/swast/.pyenv/versions/3.6.2/lib/python3.6/ssl.py”, line 636, in write
return self._sslobj.write(data)
urllib3.exceptions.ProtocolError: (‘Connection aborted.’, BrokenPipeError(32, ‘Broken pipe’))
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File “/Users/swast/src/google-cloud-python/bigquery/tests/system.py”, line 397, in test_query_many_columns
File “/Users/swast/src/google-cloud-python/api_core/google/api_core/page_iterator.py”, line 186, in _items_iter
for page in self._page_iter(increment=False):
File “/Users/swast/src/google-cloud-python/api_core/google/api_core/page_iterator.py”, line 217, in _page_iter
page = self._next_page()
File “/Users/swast/src/google-cloud-python/api_core/google/api_core/page_iterator.py”, line 336, in _next_page
response = self._get_next_page_response()
File “/Users/swast/src/google-cloud-python/api_core/google/api_core/page_iterator.py”, line 388, in _get_next_page_response
query_params=params)
File “/Users/swast/src/google-cloud-python/bigquery/google/cloud/bigquery/client.py”, line 283, in _call_api
return call()
File “/Users/swast/src/google-cloud-python/api_core/google/api_core/retry.py”, line 260, in retry_wrapped_func
on_error=on_error,
File “/Users/swast/src/google-cloud-python/api_core/google/api_core/retry.py”, line 177, in retry_target
return target()
File “/Users/swast/src/google-cloud-python/core/google/cloud/_http.py”, line 290, in api_request
headers=headers, target_object=_target_object)
File “/Users/swast/src/google-cloud-python/core/google/cloud/_http.py”, line 183, in _make_request
return self._do_request(method, url, headers, data, target_object)
File “/Users/swast/src/google-cloud-python/core/google/cloud/_http.py”, line 212, in _do_request
url=url, method=method, headers=headers, data=data)
File “/Users/swast/.pyenv/versions/3.6.2/envs/google-cloud-python/lib/python3.6/site-packages/google/auth/transport/requests.py”, line 186, in request
method, url, data=data, headers=request_headers, **kwargs)
File “/Users/swast/.pyenv/versions/3.6.2/envs/google-cloud-python/lib/python3.6/site-packages/requests/sessions.py”, line 508, in request
resp = self.send(prep, **send_kwargs)
File “/Users/swast/.pyenv/versions/3.6.2/envs/google-cloud-python/lib/python3.6/site-packages/requests/sessions.py”, line 618, in send
r = adapter.send(request, **kwargs)
File “/Users/swast/.pyenv/versions/3.6.2/envs/google-cloud-python/lib/python3.6/site-packages/requests/adapters.py”, line 490, in send
raise ConnectionError(err, request=request)
requests.exceptions.ConnectionError: (‘Connection aborted.’, BrokenPipeError(32, ‘Broken pipe’))

With 1,000 columns the request goes through but fails with the described error 413.

Error 413 (Request Entity Too Large)!!1

_______________________________________________________ TestBigQuery.test_list_rows_many_columns ________________________________________________________ Traceback (most recent call last): File "/Users/swast/src/google-cloud-python/bigquery/tests/system.py", line 382, in test_list_rows_many_columns rows = list(Config.CLIENT.list_rows(table_ref, selected_fields=schema)) File "/Users/swast/src/google-cloud-python/api_core/google/api_core/page_iterator.py", line 186, in _items_iter for page in self._page_iter(increment=False): File "/Users/swast/src/google-cloud-python/api_core/google/api_core/page_iterator.py", line 217, in _page_iter page = self._next_page() File "/Users/swast/src/google-cloud-python/api_core/google/api_core/page_iterator.py", line 336, in _next_page response = self._get_next_page_response() File "/Users/swast/src/google-cloud-python/api_core/google/api_core/page_iterator.py", line 388, in _get_next_page_response query_params=params) File "/Users/swast/src/google-cloud-python/bigquery/google/cloud/bigquery/client.py", line 283, in _call_api return call() File "/Users/swast/src/google-cloud-python/api_core/google/api_core/retry.py", line 260, in retry_wrapped_func on_error=on_error, File "/Users/swast/src/google-cloud-python/api_core/google/api_core/retry.py", line 177, in retry_target return target() File "/Users/swast/src/google-cloud-python/core/google/cloud/_http.py", line 293, in api_request raise exceptions.from_http_response(response) google.api_core.exceptions.GoogleAPICallError: 413 GET https://www.googleapis.com/bigquery/v2/projects/swast-scratch/datasets/list_rows_1519325955869/tables/many_columns/data?selectedFields=column_0_with_long_name%2Ccolumn_1_with_long_name%2Ccolumn_2_with_long_name%2Ccolumn_3_with_long_name%2Ccolumn_4_with_long_name%2Ccolumn_5_with_long_name%2Ccolumn_6_with_long_name%2Ccolumn_7_with_long_name%2Ccolumn_8_with_long_name%2Ccolumn_9_with_long_name%2Ccolumn_10_with_long_name%2Ccolumn_11_with_long_name%2Ccolumn_12_with_long_name%2Ccolumn_13_with_long_name%2Ccolumn_14_with_long_name%2Ccolumn_15_with_long_name%2Ccolumn_16_with_long_name%2Ccolumn_17_with_long_name%2Ccolumn_18_with_long_name%2Ccolumn_19_with_long_name%2Ccolumn_20_with_long_name%2Ccolumn_21_with_long_name%2Ccolumn_22_with_long_name%2Ccolumn_23_with_long_name%2Ccolumn_24_with_long_name%2Ccolumn_25_with_long_name%2Ccolumn_26_with_long_name%2Ccolumn_27_with_long_name%2Ccolumn_28_with_long_name%2Ccolumn_29_with_long_name%2Ccolumn_30_with_long_name%2Ccolumn_31_with_long_name%2Ccolumn_32_with_long_name%2Ccolumn_33_with_long_name%2Ccolumn_34_with_long_name%2Ccolumn_35_with_long_name%2Ccolumn_36_with_long_name%2Ccolumn_37_with_long_name%2Ccolumn_38_with_long_name%2Ccolumn_39_with_long_name%2Ccolumn_40_with_long_name%2Ccolumn_41_with_long_name%2Ccolumn_42_with_long_name%2Ccolumn_43_with_long_name%2Ccolumn_44_with_long_name%2Ccolumn_45_with_long_name%2Ccolumn_46_with_long_name%2Ccolumn_47_with_long_name%2Ccolumn_48_with_long_name%2Ccolumn_49_with_long_name%2Ccolumn_50_with_long_name%2Ccolumn_51_with_long_name%2Ccolumn_52_with_long_name%2Ccolumn_53_with_long_name%2Ccolumn_54_with_long_name%2Ccolumn_55_with_long_name%2Ccolumn_56_with_long_name%2Ccolumn_57_with_long_name%2Ccolumn_58_with_long_name%2Ccolumn_59_with_long_name%2Ccolumn_60_with_long_name%2Ccolumn_61_with_long_name%2Ccolumn_62_with_long_name%2Ccolumn_63_with_long_name%2Ccolumn_64_with_long_name%2Ccolumn_65_with_long_name%2Ccolumn_66_with_long_name%2Ccolumn_67_with_long_name%2Ccolumn_68_with_long_name%2Ccolumn_69_with_long_name%2Ccolumn_70_with_long_name%2Ccolumn_71_with_long_name%2Ccolumn_72_with_long_name%2Ccolumn_73_with_long_name%2Ccolumn_74_with_long_name%2Ccolumn_75_with_long_name%2Ccolumn_76_with_long_name%2Ccolumn_77_with_long_name%2Ccolumn_78_with_long_name%2Ccolumn_79_with_long_name%2Ccolumn_80_with_long_name%2Ccolumn_81_with_long_name%2Ccolumn_82_with_long_name%2Ccolumn_83_with_long_name%2Ccolumn_84_with_long_name%2Ccolumn_85_with_long_name%2Ccolumn_86_with_long_name%2Ccolumn_87_with_long_name%2Ccolumn_88_with_long_name%2Ccolumn_89_with_long_name%2Ccolumn_90_with_long_name%2Ccolumn_91_with_long_name%2Ccolumn_92_with_long_name%2Ccolumn_93_with_long_name%2Ccolumn_94_with_long_name%2Ccolumn_95_with_long_name%2Ccolumn_96_with_long_name%2Ccolumn_97_with_long_name%2Ccolumn_98_with_long_name%2Ccolumn_99_with_long_name%2Ccolumn_100_with_long_name%2Ccolumn_101_with_long_name%2Ccolumn_102_with_long_name%2Ccolumn_103_with_long_name%2Ccolumn_104_with_long_name%2Ccolumn_105_with_long_name%2Ccolumn_106_with_long_name%2Ccolumn_107_with_long_name%2Ccolumn_108_with_long_name%2Ccolumn_109_with_long_name%2Ccolumn_110_with_long_name%2Ccolumn_111_with_long_name%2Ccolumn_112_with_long_name%2Ccolumn_113_with_long_name%2Ccolumn_114_with_long_name%2Ccolumn_115_with_long_name%2Ccolumn_116_with_long_name%2Ccolumn_117_with_long_name%2Ccolumn_118_with_long_name%2Ccolumn_119_with_long_name%2Ccolumn_120_with_long_name%2Ccolumn_121_with_long_name%2Ccolumn_122_with_long_name%2Ccolumn_123_with_long_name%2Ccolumn_124_with_long_name%2Ccolumn_125_with_long_name%2Ccolumn_126_with_long_name%2Ccolumn_127_with_long_name%2Ccolumn_128_with_long_name%2Ccolumn_129_with_long_name%2Ccolumn_130_with_long_name%2Ccolumn_131_with_long_name%2Ccolumn_132_with_long_name%2Ccolumn_133_with_long_name%2Ccolumn_134_with_long_name%2Ccolumn_135_with_long_name%2Ccolumn_136_with_long_name%2Ccolumn_137_with_long_name%2Ccolumn_138_with_long_name%2Ccolumn_139_with_long_name%2Ccolumn_140_with_long_name%2Ccolumn_141_with_long_name%2Ccolumn_142_with_long_name%2Ccolumn_143_with_long_name%2Ccolumn_144_with_long_name%2Ccolumn_145_with_long_name%2Ccolumn_146_with_long_name%2Ccolumn_147_with_long_name%2Ccolumn_148_with_long_name%2Ccolumn_149_with_long_name%2Ccolumn_150_with_long_name%2Ccolumn_151_with_long_name%2Ccolumn_152_with_long_name%2Ccolumn_153_with_long_name%2Ccolumn_154_with_long_name%2Ccolumn_155_with_long_name%2Ccolumn_156_with_long_name%2Ccolumn_157_with_long_name%2Ccolumn_158_with_long_name%2Ccolumn_159_with_long_name%2Ccolumn_160_with_long_name%2Ccolumn_161_with_long_name%2Ccolumn_162_with_long_name%2Ccolumn_163_with_long_name%2Ccolumn_164_with_long_name%2Ccolumn_165_with_long_name%2Ccolumn_166_with_long_name%2Ccolumn_167_with_long_name%2Ccolumn_168_with_long_name%2Ccolumn_169_with_long_name%2Ccolumn_170_with_long_name%2Ccolumn_171_with_long_name%2Ccolumn_172_with_long_name%2Ccolumn_173_with_long_name%2Ccolumn_174_with_long_name%2Ccolumn_175_with_long_name%2Ccolumn_176_with_long_name%2Ccolumn_177_with_lon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<!DOCTYPE html> <html lang=en> <meta charset=utf-8> <meta name=viewport content="initial-scale=1, minimum-scale=1, width=device-width"> <title>Error 413 (Request Entity Too Large)!!1</title> <style> *{margin:0;padding:0}html,code{font:15px/22px arial,sans-serif}html{background:#fff;color:#222;padding:15px}body{margin:7% auto 0;max-width:390px;min-height:180px;padding:30px 0 15px}* > body{background:url(//www.google.com/images/errors/robot.png) 100% 5px no-repeat;padding-right:205px}p{margin:11px 0 22px;overflow:hidden}ins{color:#777;text-decoration:none}a img{border:0}@media screen and (max-width:772px){body{background:none;margin-top:0;max-width:none;padding-right:0}}#logo{background:url(//www.google.com/images/branding/googlelogo/1x/googlelogo_color_150x54dp.png) no-repeat;margin-left:-5px}@media only screen and (min-resolution:192dpi){#logo{background:url(//www.google.com/images/branding/googlelogo/2x/googlelogo_color_150x54dp.png) no-repeat 0% 0%/100% 100%;-moz-border-image:url(//www.google.com/images/branding/googlelogo/2x/googlelogo_color_150x54dp.png) 0}}@media only screen and (-webkit-min-device-pixel-ratio:2){#logo{background:url(//www.google.com/images/branding/googlelogo/2x/googlelogo_color_150x54dp.png) no-repeat;-webkit-background-size:100% 100%}}#logo{display:inline-block;height:54px;width:150px} </style> <span id=logo aria-label=Google></span> 413. That’s an error.

Your client issued a request that was too large. <script> (function() { var c=function(a,d,b){a=a+"=deleted"+("; path="+d);null!=b&&(a+="; domain="+b);document.cookie=a+"; expires=Thu, 01 Jan 1970 00:00:00 GMT"};var g=function(a){var d=e,b=location.hostname;c(d,a,null);c(d,a,b);for(var f=0;;){f=b.indexOf(".",f+1);if(0>f)break;c(d,a,b.substring(f+1))}};var h;if(4E3<unescape(encodeURI(document.cookie)).length){for(var k=document.cookie.split(";"),l=[],m=0;m<k.length;m++){var n=k[m].match(/^\s*([^=]+)/);n&&l.push(n[1])}for(var p=0;p<l.length;p++){var e=l[p];g("/");for(var q=location.pathname,r=0;;){r=q.indexOf("/",r+1);if(0>r)break;var t=q.substring(0,r);g(t);g(t+"/")}"/"!=q.charAt(q.length-1)&&(g(q),g(q+"/"))}h=!0}else h=!1; h&&setTimeout(function(){if(history.replaceState){var a=location.href;history.replaceState(null,"","/");location.replace(a)}},1E3); })(); </script> That’s all we know.

I don’t see a request size limit documented at https://cloud.google.com/bigquery/quotas#api_requests so I will file an issue internally about this.

The workaround we could possibly do in the client libraries is to not populate the selected_fields and pretend we have a complete Table object when fetching query results, but I worry this will not do the right thing if the query is written to an existing empty/non-empty destination table where the columns are not in the same order as the query.

tswast on Feb 22, 2018