设置像mysql这样的大查询变量

Question

与mysql变量类似的bigquery是什么？

SET @fromdate = '2014-01-01 00:00:00', -- dates for after 2013 
@todate='2015-01-01 00:00:00', 

@bfromdate = '2005-01-01 00:00:00', -- dates for before 2013 
@btodate = '2005-01-01 00:00:00', 

@achfromdate = '2013-01-01 00:00:00', -- dates for ACH without submit time in 2013 
@achtodate = '2013-01-01 00:00:00', 

@currency="USD"; 

Answer 1

有没有“变量” BigQuery中进行设置，但你可以添加一个功能要求：https://code.google.com/p/google-bigquery/issues/list?q=label:Feature-Request

Answer 2

你可能要考虑寻找到BigQuery的参数化查询。当使用用户输入构建查询时，BigQuery支持查询参数以帮助防止SQL注入。此功能仅适用于标准的SQL语法。

https://cloud.google.com/bigquery/docs/parameterized-queries

Answer 3

如果您使用的R或蟒蛇与吉贝API接口，并且不担心SQL注入，即得。您只是想在查询中迭代交换参数，您可能需要查看mustache模板语言（在R中可用'whisker'）。

如果您使用R，您可以使用condusco R软件包进行迭代/自动查询。下面是为完整的R脚本，将完成在查询中同时使用晶须和condusco迭代换出的参数：

library(bigrquery) 
library(condusco) 
library(whisker) 

# create a simple function that will create a query 
# using {{{mustache}}} placeholders for any parameters 

create_results_table <- function(params){ 

    destination_table <- '{{{dataset_id}}}.{{{table_prefix}}}_results_{{{year_low}}}_{{{year_high}}}' 

    query <- ' 
    SELECT * 
    FROM `bigquery-public-data.samples.gsod` 
    WHERE year > {{{year_low}}} 
     AND year <= {{{year_high}}} 
    ' 


    # use whisker to swap out {{{mustache}}} placeholders with parameters 
    query_exec(
    whisker.render(query,params), 
    project=whisker.render('{{{project}}}', params), 
    destination_table = whisker.render(destination_table,params), 
    use_legacy_sql = FALSE 
) 

} 

# create an invocation query to provide sets of parameters to create_results_table 

invocation_query <- ' 
    SELECT 
    "<YOUR PROJECT HERE>" as project, 
    "<YOUR DATASET_ID HERE>" as dataset_id, 
    "<YOUR TABLE PREFIX HERE>" as table_prefix, 
    num as year_low, 
    num+1 as year_high 
    FROM `bigquery-public-data.common_us.num_999999` 
    WHERE num BETWEEN 1992 AND 1995 
' 

# call condusco's run_pipeline_gbq to iteratively run create_results_table over invocation_query's results 

run_pipeline_gbq(
    create_results_table, 
    invocation_query, 
    project = '<YOUR PROJECT HERE>', 
    use_legacy_sql = FALSE 
)