Spark:将数据帧写入s3存储桶

时间:2018-12-04 11:22:52

标签: scala amazon-web-services apache-spark amazon-s3 apache-spark-sql

我正在尝试将DF数据写入S3存储桶。它工作正常。现在我想根据条件写入s3存储桶。

在数据帧中,我有一列作为Flag,并且其中的值是T和F。现在的条件是,如果Flag为F,则应将数据写入S3存储桶,否则为否。请在下面找到详细信息。

DF数据:

1015,2017/08,新潟,101,SW,39,1015,2017/08,山形,101,SW,10,29,74.35897435897436,11.0,F
1015,2017/08,新潟,101,SW,39,1015,2017/08,大分,101,SW,14,25,64.1025641025641,15.4,F
1015,2017/08,新潟,101,SW,39,1015,2017/08,山口,101,SW,6,33,84.61538461538461,6.6,T
1015,2017/08,新潟,101,SW,39,1015,2017/08,愛媛,101,SW,5,34,87.17948717948718,5.5,T
1015,2017/08,新潟,101,SW,39,1015,2017/08,神奈川,101,SW,114,75,192.30769230769232,125.4,F
1015,2017/08,新潟,101,SW,39,1015,2017/08,富山,101,SW,12,27,69.23076923076923,13.2,F
1015,2017/08,新潟,101,SW,39,1015,2017/08,高知,101,SW,3,36,92.3076923076923,3.3,T
1015,2017/08,新潟,101,SW,39,1015,2017/08,岩手,101,SW,11,28,71.7948717948718,12.1,F
1015,2017/08,新潟,101,SW,39,1015,2017/08,三重,101,SW,45,6,15.384615384615385,49.5,F
1015,2017/08,新潟,101,SW,39,1015,2017/08,京都,101,SW,23,16,41.02564102564102,25.3,F
1015,2017/08,新潟,101,SW,39,1015,2017/08,静岡,101,SW,32,7,17.94871794871795,35.2,F
1015,2017/08,新潟,101,SW,39,1015,2017/08,鹿児島,101,SW,18,21,53.84615384615385,19.8,F
1015,2017/08,新潟,101,SW,39,1015,2017/08,福島,101,SW,17,22,56.41025641025641,18.7,F

代码:

val df = spark.read.format("csv").option("header","true").option("inferSchema","true").load("s3a://test_system/transcation.csv")
    df.createOrReplaceTempView("data")
    val res = spark.sql("select count(*) from data")
    res.show(10)
    res.coalesce(1).write.format("csv").option("header","true").mode("Overwrite")
     .save("s3a://test_system/Output/Test_Result")
     res.createOrReplaceTempView("res1")
     val res2 = spark.sql("select distinct flag from res1 where flag = 'F'")
     if (res2 ==='F')
     {
     //writing to s3 bucket as raw data .Here transcation.csv file.
     df.write.format("csv").option("header","true").mode("Overwrite")
     .save("s3a://test_system/Output/Test_Result/rawdata")
     }

我正在尝试这种方法,但它没有将df数据导出到s3存储桶。 如何通过使用条件将数据导出/写入S3存储桶?

非常感谢您的帮助。

1 个答案:

答案 0 :(得分:1)

假设在数据框中存在“ F”标志,我假设您要写入数据框。

val df = spark.read.format("csv").option("header","true").option("inferSchema","true").load("s3a://test_system/transcation.csv")
df.createOrReplaceTempView("data")
val res = spark.sql("select count(*) from data")
res.show(10)
res.coalesce(1).write.format("csv").option("header","true").mode("Overwrite")
  .save("s3a://test_system/Output/Test_Result")
res.createOrReplaceTempView("res1")

在这里我们使用data表,因为res1表只是您在上面创建的计数表。同样从结果数据框中,我们通过使用first()函数仅选择第一行,并使用getAs[String](0)

从该行中选择第一列
val res2 = spark.sql("select distinct flag from data where flag = 'F'").first().getAs[String](0)

println("Printing out res2 = " + res2)

在这里,我们正在上面提取的字符串和字符串"F"之间进行比较。请记住,"F"是字符串,而'F'是scala中的字符。

if (res2.equals("F"))
{
  println("Inside the if loop")
  //writing to s3 bucket as raw data .Here transcation.csv file.
  df.write.format("csv").option("header","true").mode("Overwrite")
    .save("s3a://test_system/Output/Test_Result/rawdata")
}