*///将DF注册成一张表(临时视图)linesDF.createOrReplaceTempView("lines")//编写SQL//spark.sql("SQL语句") 这样写SQL代码会很难看,使用下面这种:括号内打出3个双引号回车valcountDF:DataFrame= spark.sql(""" |select |word,count(1) as wordNum |from( |select |explode(split(line,',')) as word...
*///方法二:valflatMapDS = dataset.flatMap(_.split("\\s")) flatMapDS.createTempView("t_word")//sql语句中,先执行后面的group by,再执行前面的selectspark .sql("select value as word ,count(value) from t_word group by value") .show() spark.stop() } }//结果+---+---+ | word|c...
val ds: Dataset[String] = spark.read.textFile("E:\\ideal_workspace\\spark\\day01\\words.txt") //3、对每一行的数据进行切割 import spark.implicits._ val wordDs: Dataset[String] = ds.flatMap(_.split(" ")) //wordDs.show() //4.数据查询 wordDs.groupBy("value").count().orderBy(...
PySpark 提供了 DataFrame API,它是 Spark SQL 的一部分,用于处理结构化数据。DataFrame 可以看作是表格形式的数据集,支持列式存储,提供了丰富的 SQL 查询和数据操作功能。DataFrame API 非常适合进行数据分析和ETL(提取、转换、加载)任务。 2.RDD(弹性分布式数据集) ...
word_count.py编写如下: from pyspark.sql import SparkSession import sys import os from operator import add if len(sys.argv) != 4: print("Usage: WordCount <intput directory> <number of local threads>", file=sys.stderr) exit(1) input_path, output_path, n_threads = sys.argv[1], sys...
valdf1=spark.sql("select word,count(1) as word_cnt from (select explode(split(sentence, ' ')) as word from badou.wordcount) t group by word order by word_cnt desc") 第二种方式: importorg.apache.spark.sql.SparkSessionimportorg.apache.spark.sql.functions._valspark=SparkSession.builder()...
-- spark依赖--><dependency><groupId>org.apache.spark</groupId><artifactId>spark-core_2.10</artifactId><version>${spark.version}</version></dependency><dependency><groupId>org.apache.spark</groupId><artifactId>spark-sql_2.10</artifactId><version>${spark.version}</version></dependency><!-...
spark.sql(sql).show()//使用DSL风格做WordCountwordsDS.groupBy("value").count().orderBy($"count".desc).show()/* +---+---+ |value|count| +---+---+ |hello| 4| | her| 3| | you| 2| | me| 1| +---+---+ +---+---+ |value...
spark.sql("select age,count(age) from t_person group by age").show //演示DSL风格查询 //1.查看name字段的数据 import org.apache.spark.sql.functions._ personDF.select(personDF.col("name")).show personDF.select(personDF("name")).show ...
countByValue().foreach(println) } } 方法三:aggregateByKey或者foldByKey 代码语言:javascript 复制 package com.cw.bigdata.spark.wordcount import org.apache.spark.{SparkConf, SparkContext} import org.apache.spark.rdd.RDD /** * WordCount实现第三种方式:aggregateByKey或者foldByKey * * def aggregate...