ALTER TABLE 原表 RENAME TO 目标表 14.first_value(),last_value 15.获取周几 date_format(字段(时间戳格式),'u') 16.struct字段类型 17.== select 1=='1' true select 1==1 true select 1=='2' false select 1=='jiang' 空 (\n) 18.case when a = 'xx' then 1 when a = 'yy' then...
option("header", value = true) .csv("dataset/pm_final.csv") import org.apache.spark.sql.functions._ pmFinal.cube('source, 'year) .agg(avg('pm) as "pm") .sort('source.asc_nulls_last, 'year.asc_nulls_last) .show() } @Test def cubeSql(): Unit = { val schemaFinal = ...
ALTER TABLE 原表 RENAME TO目标表 14. first_value(),last_value 15. 获取周几 date_format(字段(时间戳格式), 'u') 16. struct字段类型 17. == select 1 == '1' true select 1 == 1 true select 1 == '2' false select 1 == 'jiang' 空(\n) 18. case when a = 'xx' then 1 when...
first_value 按照时间降序排列获取第一个不为null的ua值赋值给每一条记录 代码解读 SELECT ifa, first_value(ua, true) over (PARTITION BY ifa ORDER BY time DESC) AS ua 1. 2. 代码解读 FROM tb2 1. row_number & rank 按照时间获取每条记录的排序序号,row_number不重复排序,rank出现重复排序 下面一个...
.option("inferschema", "true") .csv("file:///E:/TestFile/analyfuncdata.txt") df.show(false) df.printSchema() df.createOrReplaceTempView("table") val sql = "select * from table" ssc.sql(sql).show(false) 1. 2. 3. 4.
schema_of_json 返回json类型的schema select schema_of_json('{"c1":01, "c2":0.1}', map('allowNumericLeadingZeros', 'true', 'prefersDecimal', 'true')); to_csv struct转csv SELECT to_csv(struct('a', 1));1 named_struct只取value to_json struct转json SELECT to_json(named_struct('a'...
This function is used to obtain the value of the last data record in the window corresponding to the current row.The restrictions on using window functions are as follows
开启Ranger鉴权:spark.ranger.plugin.authorization.enable=true,同时需要修改参数“spark.sql.authorization.enabled”值为“true”。 关闭Ranger鉴权:spark.ranger.plugin.authorization.enable=false Spark2x中,spark-beeline(即连接到JDBCServer的应用)支持Ranger的IP过滤策略(即Ranger权限策略中的Policy Conditions),spark-...
unboundedpreceding$(),currentrow$()))ASnum#11L],[a#3],[b#4DESCNULLSLAST]+-SerializeFromObject[knownnotnull(assertnotnull(input[0,org.apache.spark.sql.test.SQLTestData$TestData2,true])).aASa#3,knownnotnull(assertnotnull(input[0,org.apache.spark.sql.test.SQLTestData$TestData2,true]))...
url'jdbc:redshift://redshifthost:5439/database?user=username&password=pass'); Writing data using SQL: --Create a new table, throwing an error if a table with the same name already exists:CREATETABLEmy_tableUSINGio.github.spark_redshift_community.spark.redshift ...