Preview table data

  using 
  
  Google.Api.Gax 
 
 ; 
 using 
  
 Google.Apis.Bigquery.v2.Data 
 ; 
 using 
  
  Google.Cloud.BigQuery.V2 
 
 ; 
 using 
  
 System 
 ; 
 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 
 "]}" 
 ); 
  
 } 
  
 } 
 } 
 

  import 
  
 ( 
  
 "context" 
  
 "fmt" 
  
 "io" 
  
 "cloud.google.com/go/bigquery" 
  
 "google.golang.org/api/iterator" 
 ) 
 // browseTable demonstrates reading data from a BigQuery table directly without the use of a query. 
 // For large tables, we also recommend the BigQuery Storage API. 
 func 
  
 browseTable 
 ( 
 w 
  
 io 
 . 
 Writer 
 , 
  
 projectID 
 , 
  
 datasetID 
 , 
  
 tableID 
  
 string 
 ) 
  
 error 
  
 { 
  
 // projectID := "my-project-id" 
  
 // datasetID := "mydataset" 
  
 // tableID := "mytable" 
  
 ctx 
  
 := 
  
 context 
 . 
 Background 
 () 
  
 client 
 , 
  
 err 
  
 := 
  
 bigquery 
 . 
 NewClient 
 ( 
 ctx 
 , 
  
 projectID 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "bigquery.NewClient: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 defer 
  
 client 
 . 
 Close 
 () 
  
 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 
 . 
 Fprintln 
 ( 
 w 
 , 
  
 row 
 ) 
  
 } 
  
 return 
  
 nil 
 } 
 

  import 
  
 com.google.cloud.bigquery. BigQuery 
 
 ; 
 import 
  
 com.google.cloud.bigquery. BigQuery 
. TableDataListOption 
 
 ; 
 import 
  
 com.google.cloud.bigquery. BigQueryException 
 
 ; 
 import 
  
 com.google.cloud.bigquery. BigQueryOptions 
 
 ; 
 import 
  
 com.google.cloud.bigquery. TableId 
 
 ; 
 import 
  
 com.google.cloud.bigquery. TableResult 
 
 ; 
 // Sample to directly browse a table with optional paging 
 public 
  
 class 
 BrowseTable 
  
 { 
  
 public 
  
 static 
  
 void 
  
 main 
 ( 
 String 
 [] 
  
 args 
 ) 
  
 { 
  
 // TODO(developer): Replace these variables before running the sample. 
  
 String 
  
 table 
  
 = 
  
 "MY_TABLE_NAME" 
 ; 
  
 String 
  
 dataset 
  
 = 
  
 "MY_DATASET_NAME" 
 ; 
  
 browseTable 
 ( 
 dataset 
 , 
  
 table 
 ); 
  
 } 
  
 public 
  
 static 
  
 void 
  
 browseTable 
 ( 
 String 
  
 dataset 
 , 
  
 String 
  
 table 
 ) 
  
 { 
  
 try 
  
 { 
  
 // Initialize client that will be used to send requests. This client only needs to be created 
  
 // once, and can be reused for multiple requests. 
  
 BigQuery 
  
 bigquery 
  
 = 
  
 BigQueryOptions 
 . 
 getDefaultInstance 
 (). 
 getService 
 (); 
  
 // Identify the table itself 
  
 TableId 
  
 tableId 
  
 = 
  
 TableId 
 . 
 of 
 ( 
 dataset 
 , 
  
 table 
 ); 
  
 // Page over 100 records. If you don't need pagination, remove the pageSize parameter. 
  
 TableResult 
  
 result 
  
 = 
  
 bigquery 
 . 
 listTableData 
 ( 
 tableId 
 , 
  
 TableDataListOption 
 . 
 pageSize 
 ( 
 100 
 )); 
  
 // Print the records 
  
 result 
  
 . 
 iterateAll 
 () 
  
 . 
 forEach 
 ( 
  
 row 
  
 - 
>  
 { 
  
 row 
 . 
 forEach 
 ( 
 fieldValue 
  
 - 
>  
 System 
 . 
 out 
 . 
 print 
 ( 
 fieldValue 
 . 
 toString 
 () 
  
 + 
  
 ", " 
 )); 
  
 System 
 . 
 out 
 . 
 println 
 (); 
  
 }); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Query ran successfully" 
 ); 
  
 } 
  
 catch 
  
 ( 
  BigQueryException 
 
  
 e 
 ) 
  
 { 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Query failed to run \n" 
  
 + 
  
 e 
 . 
 toString 
 ()); 
  
 } 
  
 } 
 } 
 

  // Import the Google Cloud client library using default credentials 
 const 
  
 { 
 BigQuery 
 } 
  
 = 
  
 require 
 ( 
 ' @google-cloud/bigquery 
' 
 ); 
 const 
  
 bigquery 
  
 = 
  
 new 
  
  BigQuery 
 
 (); 
 async 
  
 function 
  
 browseTable 
 () 
  
 { 
  
 // Retrieve a table's rows using manual pagination. 
  
 /** 
 * TODO(developer): Uncomment the following lines before running the sample. 
 */ 
  
 // const datasetId = 'my_dataset'; // Existing dataset 
  
 // const tableId = 'my_table'; // Table to create 
  
 const 
  
 query 
  
 = 
  
 `SELECT name, SUM(number) as total_people 
 FROM \`bigquery-public-data.usa_names.usa_1910_2013\` 
 GROUP BY name 
 ORDER BY total_people 
 DESC LIMIT 100` 
 ; 
  
 // Create table reference. 
  
 const 
  
 dataset 
  
 = 
  
 bigquery 
 . 
 dataset 
 ( 
 datasetId 
 ); 
  
 const 
  
 destinationTable 
  
 = 
  
 dataset 
 . 
 table 
 ( 
 tableId 
 ); 
  
 // For all options, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfigurationquery 
  
 const 
  
 queryOptions 
  
 = 
  
 { 
  
 query 
 : 
  
 query 
 , 
  
 destination 
 : 
  
 destinationTable 
 , 
  
 }; 
  
 // Run the query as a job 
  
 const 
  
 [ 
 job 
 ] 
  
 = 
  
 await 
  
 bigquery 
 . 
 createQueryJob 
 ( 
 queryOptions 
 ); 
  
 // For all options, see https://cloud.google.com/bigquery/docs/reference/v2/jobs/getQueryResults 
  
 const 
  
 queryResultsOptions 
  
 = 
  
 { 
  
 // Retrieve zero resulting rows. 
  
 maxResults 
 : 
  
 0 
 , 
  
 }; 
  
 // Wait for the job to finish. 
  
 await 
  
  job 
 
 . 
  getQueryResults 
 
 ( 
 queryResultsOptions 
 ); 
  
 function 
  
 manualPaginationCallback 
 ( 
 err 
 , 
  
 rows 
 , 
  
 nextQuery 
 ) 
  
 { 
  
 rows 
 . 
 forEach 
 ( 
 row 
  
 = 
>  
 { 
  
 console 
 . 
 log 
 ( 
 `name: 
 ${ 
 row 
 . 
 name 
 } 
 , 
 ${ 
 row 
 . 
 total_people 
 } 
 total people` 
 ); 
  
 }); 
  
 if 
  
 ( 
 nextQuery 
 ) 
  
 { 
  
 // More results exist. 
  
 destinationTable 
 . 
 getRows 
 ( 
 nextQuery 
 , 
  
 manualPaginationCallback 
 ); 
  
 } 
  
 } 
  
 // For all options, see https://cloud.google.com/bigquery/docs/reference/v2/tabledata/list 
  
 const 
  
 getRowsOptions 
  
 = 
  
 { 
  
 autoPaginate 
 : 
  
 false 
 , 
  
 maxResults 
 : 
  
 20 
 , 
  
 }; 
  
 // Retrieve all rows. 
  
 destinationTable 
 . 
 getRows 
 ( 
 getRowsOptions 
 , 
  
 manualPaginationCallback 
 ); 
 } 
 browseTable 
 (); 
 

  use Google\Cloud\BigQuery\BigQueryClient; 
 /** 
 * Browses the given table for data 
 * 
 * @param string $projectId The project Id of your Google Cloud Project. 
 * @param string $datasetId The BigQuery dataset ID. 
 * @param string $tableId The BigQuery table ID. 
 * @param int $startIndex Zero-based index of the starting row. 
 */ 
 function browse_table( 
 string $projectId, 
 string $datasetId, 
 string $tableId, 
 int $startIndex = 0 
 ): void { 
 // Query options 
 $maxResults = 10; 
 $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++; 
 } 
 } 
 

  from 
  
 google.cloud 
  
 import 
  bigquery 
 
 # Construct a BigQuery client object. 
 client 
 = 
  bigquery 
 
 . 
  Client 
 
 () 
 # TODO(developer): Set table_id to the ID of the table to browse data rows. 
 # table_id = "your-project.your_dataset.your_table_name" 
 # Download all rows from a table. 
 rows_iter 
 = 
 client 
 . 
  list_rows 
 
 ( 
 table_id 
 ) 
 # Make an API request. 
 # Iterate over rows to make the API requests to fetch row data. 
 rows 
 = 
 list 
 ( 
 rows_iter 
 ) 
 print 
 ( 
 "Downloaded 
 {} 
 rows from table 
 {} 
 " 
 . 
 format 
 ( 
 len 
 ( 
 rows 
 ), 
 table_id 
 )) 
 # Download at most 10 rows. 
 rows_iter 
 = 
 client 
 . 
  list_rows 
 
 ( 
 table_id 
 , 
 max_results 
 = 
 10 
 ) 
 rows 
 = 
 list 
 ( 
 rows_iter 
 ) 
 print 
 ( 
 "Downloaded 
 {} 
 rows from table 
 {} 
 " 
 . 
 format 
 ( 
 len 
 ( 
 rows 
 ), 
 table_id 
 )) 
 # Specify selected fields to limit the results to certain columns. 
 table 
 = 
 client 
 . 
  get_table 
 
 ( 
 table_id 
 ) 
 # Make an API request. 
 fields 
 = 
 table 
 . 
 schema 
 [: 
 2 
 ] 
 # First two columns. 
 rows_iter 
 = 
 client 
 . 
  list_rows 
 
 ( 
 table_id 
 , 
 selected_fields 
 = 
 fields 
 , 
 max_results 
 = 
 10 
 ) 
 print 
 ( 
 "Selected 
 {} 
 columns from table 
 {} 
 ." 
 . 
 format 
 ( 
 len 
 ( 
 rows_iter 
 . 
 schema 
 ), 
 table_id 
 )) 
 rows 
 = 
 list 
 ( 
 rows_iter 
 ) 
 print 
 ( 
 "Downloaded 
 {} 
 rows from table 
 {} 
 " 
 . 
 format 
 ( 
 len 
 ( 
 rows 
 ), 
 table_id 
 )) 
 # Print row data in tabular format. 
 rows_iter 
 = 
 client 
 . 
  list_rows 
 
 ( 
 table_id 
 , 
 max_results 
 = 
 10 
 ) 
 format_string 
 = 
 " 
 {!s:<16} 
 " 
 * 
 len 
 ( 
 rows_iter 
 . 
 schema 
 ) 
 field_names 
 = 
 [ 
 field 
 . 
 name 
 for 
 field 
 in 
 rows_iter 
 . 
 schema 
 ] 
 print 
 ( 
 format_string 
 . 
 format 
 ( 
 * 
 field_names 
 )) 
 # Prints column headers. 
 for 
 row 
 in 
 rows_iter 
 : 
 print 
 ( 
 format_string 
 . 
 format 
 ( 
 * 
 row 
 )) 
 # Prints row data. 
 

  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