Create a model

  import 
  
 com.google.cloud.bigquery. BigQuery 
 
 ; 
 import 
  
 com.google.cloud.bigquery. BigQueryException 
 
 ; 
 import 
  
 com.google.cloud.bigquery. BigQueryOptions 
 
 ; 
 import 
  
 com.google.cloud.bigquery. Job 
 
 ; 
 import 
  
 com.google.cloud.bigquery. JobInfo 
 
 ; 
 import 
  
 com.google.cloud.bigquery. QueryJobConfiguration 
 
 ; 
 // Sample to create a model 
 public 
  
 class 
 CreateModel 
  
 { 
  
 public 
  
 static 
  
 void 
  
 main 
 ( 
 String 
 [] 
  
 args 
 ) 
  
 { 
  
 // TODO(developer): Replace these variables before running the sample. 
  
 String 
  
 datasetName 
  
 = 
  
 "MY_DATASET_NAME" 
 ; 
  
 String 
  
 modelName 
  
 = 
  
 "MY_MODEL_NAME" 
 ; 
  
 String 
  
 sql 
  
 = 
  
 "CREATE MODEL `" 
  
 + 
  
 datasetName 
  
 + 
  
 "." 
  
 + 
  
 modelName 
  
 + 
  
 "`" 
  
 + 
  
 "OPTIONS ( " 
  
 + 
  
 "model_type='linear_reg', " 
  
 + 
  
 "max_iterations=1, " 
  
 + 
  
 "learn_rate=0.4, " 
  
 + 
  
 "learn_rate_strategy='constant' " 
  
 + 
  
 ") AS ( " 
  
 + 
  
 "SELECT 'a' AS f1, 2.0 AS label " 
  
 + 
  
 "UNION ALL " 
  
 + 
  
 "SELECT 'b' AS f1, 3.8 AS label " 
  
 + 
  
 ")" 
 ; 
  
 createModel 
 ( 
 sql 
 ); 
  
 } 
  
 public 
  
 static 
  
 void 
  
 createModel 
 ( 
 String 
  
 sql 
 ) 
  
 { 
  
 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 
 (); 
  
  QueryJobConfiguration 
 
  
 config 
  
 = 
  
  QueryJobConfiguration 
 
 . 
 newBuilder 
 ( 
 sql 
 ). 
 build 
 (); 
  
 // create a model using query and it will wait to complete job. 
  
  Job 
 
  
 job 
  
 = 
  
 bigquery 
 . 
  create 
 
 ( 
 JobInfo 
 . 
 of 
 ( 
 config 
 )); 
  
 job 
  
 = 
  
 job 
 . 
  waitFor 
 
 (); 
  
 if 
  
 ( 
 job 
 . 
  isDone 
 
 ()) 
  
 { 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Model created successfully" 
 ); 
  
 } 
  
 else 
  
 { 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Model was not created" 
 ); 
  
 } 
  
 } 
  
 catch 
  
 ( 
  BigQueryException 
 
  
 | 
  
 InterruptedException 
  
 e 
 ) 
  
 { 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Model was not created. \n" 
  
 + 
  
 e 
 . 
 toString 
 ()); 
  
 } 
  
 } 
 } 
 

  // Import the Google Cloud client library 
 const 
  
 { 
 BigQuery 
 } 
  
 = 
  
 require 
 ( 
 ' @google-cloud/bigquery 
' 
 ); 
 const 
  
 bigquery 
  
 = 
  
 new 
  
  BigQuery 
 
 (); 
 async 
  
 function 
  
 createModel 
 () 
  
 { 
  
 // Creates a model named "my_model" in "my_dataset". 
  
 /** 
 * TODO(developer): Uncomment the following lines before running the sample 
 */ 
  
 // const datasetId = "my_dataset"; 
  
 // const modelId = "my_model"; 
  
 const 
  
 query 
  
 = 
  
 `CREATE OR REPLACE MODEL \` 
 ${ 
 datasetId 
 } 
 . 
 ${ 
 modelId 
 } 
 \` 
 OPTIONS(model_type='logistic_reg') AS 
 SELECT 
 IF(totals.transactions IS NULL, 0, 1) AS label, 
 IFNULL(device.operatingSystem, "") AS os, 
 device.isMobile AS is_mobile, 
 IFNULL(geoNetwork.country, "") AS country, 
 IFNULL(totals.pageviews, 0) AS pageviews 
 FROM 
 \`bigquery-public-data.google_analytics_sample.ga_sessions_*\` 
 WHERE 
 _TABLE_SUFFIX BETWEEN '20160801' AND '20170631' 
 LIMIT  100000;` 
 ; 
  
 const 
  
 queryOptions 
  
 = 
  
 { 
  
 query 
 : 
  
 query 
 , 
  
 }; 
  
 // Run query to create a model 
  
 const 
  
 [ 
 job 
 ] 
  
 = 
  
 await 
  
 bigquery 
 . 
 createQueryJob 
 ( 
 queryOptions 
 ); 
  
 // Wait for the query to finish 
  
 await 
  
  job 
 
 . 
  getQueryResults 
 
 (); 
  
 console 
 . 
 log 
 ( 
 `Model 
 ${ 
 modelId 
 } 
 created.` 
 ); 
 } 
 createModel 
 ();