google-bigquery

问题 To connect to Google Cloud BigQuery that exists in a different GCP project from a Google Cloud Function, I am creating the BigQuery Client as follows: const {BigQuery} = require('@google-cloud/bigquery'); const options = { keyFilename: 'path/to/service_account.json', projectId: 'my_project', }; const bigquery = new BigQuery(options); But instead of storing the service_account.json in my Cloud Function, I want to store the Service Account in Google Cloud Storage and provide the Google Cloud

问题 how to load data from AWS RDS to Google BigQuery in streaming mode? Description: I have data in RDS (SQL Server), and wanted to load this data into Google BigQuery in real-time. 回答1: There is no direct way to insert changes from Amazon RDS to Google Cloud BigQuery. It could be done with a pipeline like this Amazon RDS ----Lambda/DMS----> Kinesis Data Streams -----Lambda----> BigQuery Read changes from Amazon RDS to Kinesis Data Streams using Lambda or use Cloud DMS. You can also push it to

问题 I have a table in Google BigQuery that I access and modify in Python using the pandas functions read_gbq and to_gbq . The problem is that appending 100,000 lines takes about 150 seconds while appending 1 line takes about 40 seconds. I would like to update a value in the table rather than append a line, is there a way to update a value in the table using python that is very fast, or faster than 40 seconds? 回答1: Not sure if you can do so using pandas but you sure can using google-cloud library.

问题 I would like to run a query that partitions table A using a value from table B. For example: #standard SQL select A.user_id from my_project.xxx A inner join my_project.yyy B on A._partitiontime = timestamp(B.date) where B.date = '2018-01-01' This query will scan all the partitions in table A and will not take into consideration the date I specified in the where clause (for partitioning purposes). I have tried running this query in several different ways but all produced the same result -

问题 I would like to run a query that partitions table A using a value from table B. For example: #standard SQL select A.user_id from my_project.xxx A inner join my_project.yyy B on A._partitiontime = timestamp(B.date) where B.date = '2018-01-01' This query will scan all the partitions in table A and will not take into consideration the date I specified in the where clause (for partitioning purposes). I have tried running this query in several different ways but all produced the same result -

问题 Below is the code to convert BigQuery results into Pandas data frame. Im learning Python&Pandas and wonder if i can get suggestion/ideas about any kind of improvements to the code? #...code to run query, that returns 3 columns: 'date' DATE, 'currency' STRING,'rate' FLOAT... rows, total_count, token = query.fetch_data() currency = [] rate = [] dates = [] for row in rows: dates.append(row[0]) currency.append(row[1]) rate.append(row[2]) dict = { 'currency' : currency, 'date' : dates, 'rate' :

问题 People, the company where I work has some MySQL databases on AWS (Amazon RDS). We are making a POC with BigQuery and what I am researching now is how to replicate the bases to BigQuery (the existing registers and the new ones in the future). My doubts are: How to replicate the MySQL tables and rows to BigQuery. Is there any tool to do that (I am reading about Amazon Database Migration Service)? Should I replicate to Google Cloud SQL and than export to BigQuery? How to replicate the future

问题 People, the company where I work has some MySQL databases on AWS (Amazon RDS). We are making a POC with BigQuery and what I am researching now is how to replicate the bases to BigQuery (the existing registers and the new ones in the future). My doubts are: How to replicate the MySQL tables and rows to BigQuery. Is there any tool to do that (I am reading about Amazon Database Migration Service)? Should I replicate to Google Cloud SQL and than export to BigQuery? How to replicate the future

问题 Is there a way to set default values for columns in tables in big query? I would like to set 'false' as a default value for a column of boolean data type. 回答1: A nullable column can (trivially) have a NULL default value, but there is no other notion of default in BigQuery (you either insert a particular value or omit the value and it will have the NULL value). That said, if you want to wrap your raw table in a View, you can map a NULL column value to any default that you like. 回答2: There is

问题 Is there a way to set default values for columns in tables in big query? I would like to set 'false' as a default value for a column of boolean data type. 回答1: A nullable column can (trivially) have a NULL default value, but there is no other notion of default in BigQuery (you either insert a particular value or omit the value and it will have the NULL value). That said, if you want to wrap your raw table in a View, you can map a NULL column value to any default that you like. 回答2: There is