spark UDAF根据某列去重求合 distinct sum
例子:
package spark.groupzbimport org.apache.log4j.{Level, Logger}
import org.apache.spark.sql.types._
import org.apache.spark.sql.{Row, SparkSession}/**
* create by roy on 2020-03020
*/
object OrderDistinctSumTest {
Logger.getRootLogger.setLevel(Level.WARN)def main(args: Array[String]): Unit = {
val data = https://www.it610.com/article/Seq(
Row("barnd1", "a", 300.0),
Row("barnd1", "a", 300.0),
Row("barnd1", "b", 200.0),
Row("barnd2", "c", 200.0),
Row("barnd2", "c", 200.0),
Row("barnd3", "c", 200.0),
Row("barnd3", "c", 200.0)
//Row("a", "400", Array(Row("a", "name_a")))
)
val schme = new StructType()
.add("barnd", StringType)
.add("orderid", StringType)
.add("price", DoubleType)
schme.printTreeString()
val spark = SparkSession.builder().master("local[*]").getOrCreate()
val df = spark.createDataFrame(spark.sparkContext.parallelize(data), schme)
df.show()
import spark.implicits._
df.createOrReplaceTempView("tmp_tab")
//spark.sql(
//"""
//|select barnd,sum(price) sum_price
//|from tmp_tab group by barnd
//""".stripMargin).show()
//println("orderDistinctSumUDAF")
val orderDistinctSumUDAF = new OrderDistinctSumUDAF
spark.sqlContext.udf.register("orderDistinctSumUDAF", orderDistinctSumUDAF)
//订单去重，求次数，订单量，金额
spark.sql(
"""
|select barnd,count(1) ct,count(distinct orderid) order_num,orderDistinctSumUDAF(orderid,price) sum_price
|from tmp_tabgroup by barnd
""".stripMargin).show()
//+------+---+---------+---------+
//| barnd| ct|order_num|sum_price|
//+------+---+---------+---------+
//|barnd3|2|1|200.0|
//|barnd2|2|1|200.0|
//|barnd1|3|2|500.0|
//+------+---+---------+---------+
//这样需再次连接求出
spark.sql(
"""
|select barnd,sum(price) pricesfrom (
|select barnd,orderid,price,count(1)
|from tmp_tab group by barnd,orderid,price
|) t1 group by barnd
""".stripMargin).show()
//+------+------+
//| barnd|prices|
//+------+------+
//|barnd3| 200.0|
//|barnd2| 200.0|
//|barnd1| 500.0|
//+------+------+//println("partition by barnd,orderid ")
//spark.sql(
//"""
//|select barnd,first_value(orderid) over(PARTITION BY orderid) lowid
//|from tmp_tab
//""".stripMargin).show()
}}
UDAF:
package spark.groupzbimport org.apache.spark.sql.Row
import org.apache.spark.sql.expressions.{MutableAggregationBuffer, UserDefinedAggregateFunction}
import org.apache.spark.sql.types._/**
* create by roy 2020-03-18
* 订单id去重，并求合
*
*/
class OrderDistinctSumUDAF extends UserDefinedAggregateFunction {override def inputSchema: StructType = {
new StructType()
//.add("barnd", StringType)
.add("orderid", StringType)
.add("sum_v", DoubleType)}override def update(buffer: MutableAggregationBuffer, input: Row): Unit = {
//println("update==>>>", buffer, input) //餐品 有多少个订单
val orderid = input.getAs[String](0)
val sum_v = input.getAs[Double](1)
//取出新加入的行，并加入缓存区
//buffer(0) = buffer.getSeq[String](0) ++ orderid
buffer(0) =Seq[String](orderid)
buffer(1) = buffer.getAs[Double](1) + sum_v}override def bufferSchema: StructType = {
//new StructType().add("items", ArrayType(new StructType().add("orderid", StringType).add("sumv", DoubleType), true), nullable = true)
new StructType().add("orderid", ArrayType(StringType)).add("sumv", DoubleType)
}//合并数据
override def merge(buffer1: MutableAggregationBuffer, buffer2: Row): Unit = {
//println("merge==>", buffer1, "|", buffer2)
val b1Seq = buffer1.getSeq[String](0)
val orderid=buffer2.getSeq[String](0)(0)//第1列，第1个元素
if (!b1Seq.contains(orderid)) {
buffer1(0) = b1Seq ++ orderid
buffer1(1) = buffer1.getAs[Double](1) + buffer2.getAs[Double](1)
}
}override def initialize(buffer: MutableAggregationBuffer): Unit = {
buffer(0) = Seq[String]()
buffer(1) = 0.0}override def deterministic: Boolean = trueoverride def evaluate(buffer: Row): Any = {
//buffer.getSeq[String](0).length
buffer.getAs[Double](1)
}override def dataType: DataType = DoubleTypecase class ObjetValus(orderId: String, sumV: Double)}输出:
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D:\tools\mavenRepository\org\apache\hbase\hbase-metrics-api\1.4.10\hbase-metrics-api-1.4.10.jar;
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D:\tools\mavenRepository\org\jamon\jamon-runtime\2.4.1\jamon-runtime-2.4.1.jar;
D:\tools\mavenRepository\com\lmax\disruptor\3.3.0\disruptor-3.3.0.jar;
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D:\tools\mavenRepository\org\apache\httpcomponents\httpcore\4.4.4\httpcore-4.4.4.jar;
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D:\tools\mavenRepository\org\apache\hadoop\hadoop-mapreduce-client-app\2.7.4\hadoop-mapreduce-client-app-2.7.4.jar;
D:\tools\mavenRepository\org\apache\hadoop\hadoop-mapreduce-client-common\2.7.4\hadoop-mapreduce-client-common-2.7.4.jar;
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D:\tools\mavenRepository\org\apache\hadoop\hadoop-yarn-server-common\2.7.4\hadoop-yarn-server-common-2.7.4.jar;
D:\tools\mavenRepository\org\apache\hadoop\hadoop-mapreduce-client-shuffle\2.7.4\hadoop-mapreduce-client-shuffle-2.7.4.jar;
D:\tools\mavenRepository\org\apache\hadoop\hadoop-yarn-api\2.7.4\hadoop-yarn-api-2.7.4.jar;
D:\tools\mavenRepository\org\apache\hadoop\hadoop-mapreduce-client-jobclient\2.7.4\hadoop-mapreduce-client-jobclient-2.7.4.jar;
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D:\tools\mavenRepository\org\fusesource\leveldbjni\leveldbjni-all\1.8\leveldbjni-all-1.8.jar;
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D:\tools\mavenRepository\org\spark-project\hive\hive-ant\1.2.1.spark2\hive-ant-1.2.1.spark2.jar;
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D:\tools\mavenRepository\org\spark-project\hive\shims\hive-shims-common\1.2.1.spark2\hive-shims-common-1.2.1.spark2.jar;
D:\tools\mavenRepository\org\spark-project\hive\shims\hive-shims-0.20S\1.2.1.spark2\hive-shims-0.20S-1.2.1.spark2.jar;
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D:\tools\mavenRepository\javax\inject\javax.inject\1\javax.inject-1.jar;
D:\tools\mavenRepository\aopalliance\aopalliance\1.0\aopalliance-1.0.jar;
D:\tools\mavenRepository\com\sun\jersey\jersey-json\1.9\jersey-json-1.9.jar;
D:\tools\mavenRepository\com\sun\xml\bind\jaxb-impl\2.2.3-1\jaxb-impl-2.2.3-1.jar;
D:\tools\mavenRepository\org\codehaus\jackson\jackson-xc\1.8.3\jackson-xc-1.8.3.jar;
D:\tools\mavenRepository\com\sun\jersey\contribs\jersey-guice\1.9\jersey-guice-1.9.jar;
D:\tools\mavenRepository\org\codehaus\jettison\jettison\1.1\jettison-1.1.jar;
D:\tools\mavenRepository\com\sun\jersey\jersey-client\1.9\jersey-client-1.9.jar;
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D:\tools\mavenRepository\org\apache\hadoop\hadoop-yarn-server-web-proxy\2.6.0\hadoop-yarn-server-web-proxy-2.6.0.jar;
D:\tools\mavenRepository\org\spark-project\hive\shims\hive-shims-scheduler\1.2.1.spark2\hive-shims-scheduler-1.2.1.spark2.jar;
D:\tools\mavenRepository\org\spark-project\hive\spark-client\1.2.1.spark2\spark-client-1.2.1.spark2.jar;
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D:\tools\mavenRepository\org\apache\spark\spark-network-common_2.10\1.3.1\spark-network-common_2.10-1.3.1.jar;
D:\tools\mavenRepository\org\apache\spark\spark-network-shuffle_2.10\1.3.1\spark-network-shuffle_2.10-1.3.1.jar;
D:\tools\mavenRepository\net\java\dev\jets3t\jets3t\0.7.1\jets3t-0.7.1.jar;
D:\tools\mavenRepository\org\eclipse\jetty\orbit\javax.servlet\3.0.0.v201112011016\javax.servlet-3.0.0.v201112011016.jar;
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D:\tools\mavenRepository\org\spark-project\akka\akka-remote_2.10\2.3.4-spark\akka-remote_2.10-2.3.4-spark.jar;
D:\tools\mavenRepository\org\spark-project\akka\akka-actor_2.10\2.3.4-spark\akka-actor_2.10-2.3.4-spark.jar;
D:\tools\mavenRepository\com\typesafe\config\1.2.1\config-1.2.1.jar;
D:\tools\mavenRepository\org\spark-project\protobuf\protobuf-java\2.5.0-spark\protobuf-java-2.5.0-spark.jar;
D:\tools\mavenRepository\org\uncommons\maths\uncommons-maths\1.2.2a\uncommons-maths-1.2.2a.jar;
D:\tools\mavenRepository\org\spark-project\akka\akka-slf4j_2.10\2.3.4-spark\akka-slf4j_2.10-2.3.4-spark.jar;
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D:\tools\mavenRepository\org\json4s\json4s-ast_2.10\3.2.10\json4s-ast_2.10-3.2.10.jar;
D:\tools\mavenRepository\org\scala-lang\scalap\2.10.0\scalap-2.10.0.jar;
D:\tools\mavenRepository\org\scala-lang\scala-compiler\2.10.0\scala-compiler-2.10.0.jar;
D:\tools\mavenRepository\org\apache\mesos\mesos\0.21.0\mesos-0.21.0-shaded-protobuf.jar;
D:\tools\mavenRepository\com\fasterxml\jackson\module\jackson-module-scala_2.10\2.4.4\jackson-module-scala_2.10-2.4.4.jar;
D:\tools\mavenRepository\org\tachyonproject\tachyon-client\0.5.0\tachyon-client-0.5.0.jar;
D:\tools\mavenRepository\org\tachyonproject\tachyon\0.5.0\tachyon-0.5.0.jar;
D:\tools\mavenRepository\org\spark-project\pyrolite\2.0.1\pyrolite-2.0.1.jar;
D:\tools\mavenRepository\javolution\javolution\5.5.1\javolution-5.5.1.jar;
D:\tools\mavenRepository\log4j\apache-log4j-extras\1.2.17\apache-log4j-extras-1.2.17.jar;
D:\tools\mavenRepository\org\antlr\antlr-runtime\3.4\antlr-runtime-3.4.jar;
D:\tools\mavenRepository\org\antlr\stringtemplate\3.2.1\stringtemplate-3.2.1.jar;
D:\tools\mavenRepository\antlr\antlr\2.7.7\antlr-2.7.7.jar;
D:\tools\mavenRepository\org\antlr\ST4\4.0.4\ST4-4.0.4.jar;
D:\tools\mavenRepository\org\apache\ant\ant\1.9.1\ant-1.9.1.jar;
D:\tools\mavenRepository\org\apache\ant\ant-launcher\1.9.1\ant-launcher-1.9.1.jar;
D:\tools\mavenRepository\org\codehaus\groovy\groovy-all\2.1.6\groovy-all-2.1.6.jar;
D:\tools\mavenRepository\com\googlecode\javaewah\JavaEWAH\0.3.2\JavaEWAH-0.3.2.jar;
D:\tools\mavenRepository\org\iq80\snappy\snappy\0.2\snappy-0.2.jar;
D:\tools\mavenRepository\org\json\json\20090211\json-20090211.jar;
D:\tools\mavenRepository\stax\stax-api\1.0.1\stax-api-1.0.1.jar;
D:\tools\mavenRepository\net\sf\opencsv\opencsv\2.3\opencsv-2.3.jar;
D:\tools\mavenRepository\jline\jline\2.12\jline-2.12.jar;
D:\tools\mavenRepository\org\slf4j\slf4j-log4j12\1.7.5\slf4j-log4j12-1.7.5.jar;
D:\tools\mavenRepository\io\netty\netty-all\4.1.18.Final\netty-all-4.1.18.Final.jar;
D:\tools\mavenRepository\io\delta\delta-core_2.11\0.4.0\delta-core_2.11-0.4.0.jar;
D:\tools\mavenRepository\org\scala-lang\scala-library\2.11.12\scala-library-2.11.12.jar;
D:\tools\mavenRepository\org\antlr\antlr4\4.7\antlr4-4.7.jar;
D:\tools\mavenRepository\org\abego\treelayout\org.abego.treelayout.core\1.0.3\org.abego.treelayout.core-1.0.3.jar;
D:\tools\mavenRepository\org\glassfish\javax.json\1.0.4\javax.json-1.0.4.jar;
D:\tools\mavenRepository\com\ibm\icu\icu4j\58.2\icu4j-58.2.jar;
D:\tools\mavenRepository\org\antlr\antlr4-runtime\4.7\antlr4-runtime-4.7.jar" spark.groupzb.OrderDistinctSumTest
root
|-- barnd: string (nullable = true)
|-- orderid: string (nullable = true)
|-- price: double (nullable = true)20/03/20 00:07:03 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
+------+-------+-----+
| barnd|orderid|price|
+------+-------+-----+
|barnd1|a|300.0|
|barnd1|a|300.0|
|barnd1|b|200.0|
|barnd2|c|200.0|
|barnd2|c|200.0|
|barnd3|c|200.0|
|barnd3|c|200.0|
+------+-------+-----++------+---+---------+---------+
| barnd| ct|order_num|sum_price|
+------+---+---------+---------+
|barnd3|2|1|200.0|
|barnd2|2|1|200.0|
|barnd1|3|2|500.0|
+------+---+---------+---------+【spark|spark UDAF根据某列去重求合 distinct sum】
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