{"id":8755,"date":"2021-05-29T11:18:11","date_gmt":"2021-05-29T11:18:11","guid":{"rendered":"https:\/\/prwatech.in\/blog\/?p=8755"},"modified":"2024-03-19T09:14:41","modified_gmt":"2024-03-19T09:14:41","slug":"data-fusion-with-bigquery","status":"publish","type":"post","link":"https:\/\/prwatech.in\/blog\/google-cloud-platform\/bigquery\/data-fusion-with-bigquery\/","title":{"rendered":"Data Fusion with BigQuery"},"content":{"rendered":"\r\n

Cloud Data Fusion and BigQuery for data integration<\/h2>\r\n

 <\/p>\r\n

Prerequisites<\/strong><\/p>\r\n\r\n\r\n\r\n

GCP<\/a> account<\/p>\r\n\r\n\r\n\r\n

Open Console.<\/p>\r\n\r\n\r\n\r\n

Click on Activate cloud shell<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

$\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 echo $GOOGLE_CLOUD_PROJECT\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 #Display the Project ID<\/p>\r\n\r\n\r\n\r\n

$\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 gsutil cp gs:\/\/cloud-training\/OCBL017\/ny-taxi-2018-sample.csv gs:\/\/$GOOGLE_CLOUD_PROJECT\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0<\/p>\r\n\r\n\r\n\r\n

#Copying file from cloud training public bucket into our bucket<\/p>\r\n\r\n\r\n\r\n

$\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 gsutil mb gs:\/\/$GOOGLE_CLOUD_PROJECT-temp\u00a0\u00a0 #Creating bucket<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Open\u00a0 Menu > Cloud Storage > Browser<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

The temporary\u00a0bucket is created<\/a> and the file is copied in main bucket.<\/p>\r\n\r\n\r\n\r\n

Open Menu > Data Fusion<\/a><\/p>\r\n\r\n\r\n\r\n

Click on View Instance. It will open the Data Fusion page.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Click No thanks.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Click on Wrangler<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

In Default Cloud Storage > Open the bucket which we copied the file.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Select the copied file.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Click on drop down arrow.<\/h3>\r\n\r\n\r\n\r\n
\"\"<\/figure>\r\n\r\n\r\n\r\n

Click Parse > CSV<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Select comma and tick set first row as header.<\/p>\r\n\r\n\r\n\r\n

Click Apply<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

In drop down of body column, Click delete column<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

In Trip distance drop down > change data type to Float<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

\u00a0open Filter > Custom condition<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Give Condition as >0.0<\/p>\r\n\r\n\r\n\r\n

Click Apply<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

In right side of table, we can see the transformations which we did in our table<\/p>\r\n\r\n\r\n\r\n

Then Click on Create a pipeline<\/h3>\r\n

 <\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Click on Batch Pipeline.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

It will create a Pipeline.<\/p>\r\n\r\n\r\n\r\n

properties in Wrangler<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

The modifications done in table will be already mentioned in here<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

In right side, output schema is visible. In that delete column named extra.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Validate.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Click on close if no errors found.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Open \u00a0Console > BigQuery<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Click Create dataset.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Give dataset name. Click Create Dataset.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Click on More > Query Settings<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Select Set destination table for query results.<\/p>\r\n\r\n\r\n\r\n

Give Project name,Dataset name, and table name.<\/p>\r\n\r\n\r\n\r\n

Select Write if empty or Overwrite table and press save.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Click save<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

In Query Editor, Paste the below code<\/p>\r\n\r\n\r\n\r\n

SELECT<\/p>\r\n\r\n\r\n\r\n

\u00a0 zone_id,<\/p>\r\n\r\n\r\n\r\n

\u00a0 zone_name,<\/p>\r\n\r\n\r\n\r\n

\u00a0 borough<\/p>\r\n\r\n\r\n\r\n

FROM<\/p>\r\n\r\n\r\n\r\n

\u00a0 bigquery-public-data.new_york_taxi_trips.taxi_zone_geom<\/p>\r\n\r\n\r\n\r\n

Click Run<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

The output will be saved in the created table.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Go back to Data Fusion<\/p>\r\n\r\n\r\n\r\n

\u00a0Source > BigQuery<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Properties in BigQuery.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Reference name.<\/p>\r\n\r\n\r\n\r\n

Give the dataset name and table name which we created.<\/p>\r\n\r\n\r\n\r\n

Click Get schema<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

The Output Schema will be displayed in Right side.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Temporary bucket name.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Click on Validate.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

if no errors found.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Click Analytics > Joiner<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Drag the arrow into joiner from both BigQuery and Wrangler.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n
\"\"<\/figure>\r\n\r\n\r\n\r\n

Click on properties in joiner<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Jointype : inner<\/p>\r\n\r\n\r\n\r\n

Join condition<\/strong><\/p>\r\n\r\n\r\n\r\n

Wrangler : pickup_location_id<\/p>\r\n\r\n\r\n\r\n

BigQuery : zone_id<\/p>\r\n\r\n\r\n\r\n

Click on Get Schema.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

In output schema remove pickup_location_id & zone_id<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

remove zone_id.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Validate.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

close if no errors found.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Sink > bigQuery<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

properties in second big query.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Give Reference name, dataset, table name.<\/p>\r\n\r\n\r\n\r\n

Give the temporary bucket name which we created.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Click on Validate.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

close if no errors found<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Now drag the arrow from Joiner<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

rename the pipeline. Click save<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Save.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Deploy<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

It will deploy pipeline<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Click run.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

It will Start Execution. This execution will take arround 10-15 minutes.<\/p>\r\n\r\n\r\n\r\n

Execution is Provisioning<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

\u00a0Starting<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Running<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

\u00a0Finished Successfully.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

Go to BigQuery. In the dataset, new table will be created.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n\r\n\r\n\r\n

In the data Fusion, Click Logs.You can see the logs of Execution.<\/p>\r\n\r\n\r\n\r\n

\"\"<\/figure>\r\n

 <\/p>\r\n

Cloud Data Fusion and BigQuery for data integration<\/p>\r\n

 <\/p>\r\n","protected":false},"excerpt":{"rendered":"

Cloud Data Fusion and BigQuery for data integration   Prerequisites GCP account Open Console. Click on Activate cloud shell $\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 echo $GOOGLE_CLOUD_PROJECT\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 #Display the Project ID $\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 gsutil cp gs:\/\/cloud-training\/OCBL017\/ny-taxi-2018-sample.csv gs:\/\/$GOOGLE_CLOUD_PROJECT\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 #Copying file from cloud training public bucket into our bucket $\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 gsutil mb gs:\/\/$GOOGLE_CLOUD_PROJECT-temp\u00a0\u00a0 #Creating bucket Open\u00a0 Menu > Cloud Storage > Browser […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1632,1],"tags":[728,1401,1403,732,1402,1408,1407,1405,1406,605,729,641,699,700,984,617,683,684,685,611,1400,692],"class_list":["post-8755","post","type-post","status-publish","format-standard","hentry","category-bigquery","category-google-cloud-platform","tag-bigquery","tag-bigquery-console","tag-bigquery-documentation","tag-bigquery-sql","tag-bigquery-tutorial","tag-data-fusion-documentation","tag-data-fusion-examples","tag-data-fusion-techniques","tag-data-fusion-tutorial","tag-gcp","tag-gcp-bigquery","tag-gcp-bucket","tag-gcp-certification","tag-gcp-cloud-console","tag-gcp-course","tag-google-cloud","tag-google-cloud-certification","tag-google-cloud-console","tag-google-cloud-courses","tag-google-cloud-platform","tag-google-cloud-platform-tutorial","tag-google-cloud-training"],"acf":[],"yoast_head":"\nCloud Data Fusion and BigQuery for data integration - prwatech<\/title>\n<meta name=\"description\" content=\"Master Cloud Data Fusion and BigQuery with Prwatech - Dive deep with our expert instructors and comprehensive curriculum.\" \/>\n<meta name=\"robots\" content=\"noindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Cloud Data Fusion and BigQuery for data integration - prwatech\" \/>\n<meta property=\"og:description\" content=\"Master Cloud Data Fusion and BigQuery with Prwatech - Dive deep with our expert instructors and comprehensive curriculum.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/prwatech.in\/blog\/google-cloud-platform\/bigquery\/data-fusion-with-bigquery\/\" \/>\n<meta property=\"og:site_name\" content=\"Prwatech\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/prwatech.in\/\" \/>\n<meta property=\"article:published_time\" content=\"2021-05-29T11:18:11+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-03-19T09:14:41+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/prwatech.in\/blog\/wp-content\/uploads\/2021\/05\/image-156.png\" \/>\n<meta name=\"author\" content=\"Prwatech\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@Eduprwatech\" \/>\n<meta name=\"twitter:site\" content=\"@Eduprwatech\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Prwatech\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"15 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/prwatech.in\/blog\/google-cloud-platform\/bigquery\/data-fusion-with-bigquery\/\",\"url\":\"https:\/\/prwatech.in\/blog\/google-cloud-platform\/bigquery\/data-fusion-with-bigquery\/\",\"name\":\"Cloud Data Fusion and BigQuery for data integration - 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