BigQuery with data analysis function - now and in real time

Businesses are constantly receiving huge amounts of data from network applications that commit multiple transactions, serving millions of people and the ever-growing number of connected devices. The most important condition for maintaining competitiveness is the ability to quickly respond to changes in this data. At the same time, companies are engaged in collecting, storing and analyzing large amounts of information, sometimes hundreds of gigabytes per day, using systems that are simply not able to cope with a similar pace of work.

We created BigQuery to help businesses deal with this problem without having to invest in complex, expensive equipment. We present two new features that can simplify their task.

Real-time streaming

Now you can transfer data record by record using a simple API call - tabledata().insertAll() . This will allow you to load them as they arrive, instead of creating and maintaining systems for caching and subsequent data transfer in series. And the most important thing is that the data immediately become available for analysis.

Streaming data in BigQuery is easy. This is an example for Python:
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 body = {"rows":[ {"json": {"column_name":7.7,}} ]} response = bigquery.tabledata().insertAll( projectId=PROJECT_ID, datasetId=DATASET_ID, tableId=TABLE_ID, body=body).execute() 

The possibility of streaming data is provided free of charge during the evaluation period until January 1, 2014. After that, the provision of services will be charged at a rate of 1 cent for 10 thousand entered entries. The existing batch data entry system will remain free.

Analysis of the table subset

It became possible to selectively analyze certain subsets of a table using a simple new @ SQL . , , 24 , . , , 30 .

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