Question

我有以下json格式：

{"Request": {"TrancheList": {"Tranche": [{"TrancheId": "500192163","OwnedAmt": "26500000",    "Curr": "USD" }, {  "TrancheId": "500213369", "OwnedAmt": "41000000","Curr": "USD"}]},"FxRatesList": {"FxRatesContract": [{"Currency": "CHF","FxRate": "0.97919983706115"},{"Currency": "AUD", "FxRate": "1.2966804979253"},{ "Currency": "USD","FxRate": "1"},{"Currency": "SEK","FxRate": "8.1561012531034"},{"Currency": "NOK", "FxRate": "8.2454981641398"},{"Currency": "JPY","FxRate": "111.79999785344"},{"Currency": "HKD","FxRate": "7.7568025218916"},{"Currency": "GBP","FxRate": "0.69425159677867"}, {"Currency": "EUR","FxRate": "0.88991723769689"},{"Currency": "DKK", "FxRate": "6.629598372301"}]},"isExcludeDeals": "true","baseCurrency": "USD"}}

从hdfs：

读取json

val hdfsRequest = spark.read.json("hdfs://localhost/user/request.json")
val baseCurrency = hdfsRequest.select("Request.baseCurrency").map(_.getString(0)).collect.headOption
var fxRates = hdfsRequest.select("Request.FxRatesList.FxRatesContract")
val fxRatesDF = fxRates.select(explode(fxRates("FxRatesContract"))).toDF("FxRatesContract").select("FxRatesContract.Currency", "FxRatesContract.FxRate").filter($"Currency"===baseCurrency.get)
fxRatesDF.show()

我为fxRatesDF获取的输出是：

fxRatesDF: org.apache.spark.sql.Dataset[org.apache.spark.sql.Row] = [Currency: string, FxRate: string]
+--------+------+
|Currency|FxRate|
+--------+------+
|     USD|     1|

如何获取Fxrate列第一行的值？

Answer 1

您可以使用

fxRatesDF.select(col("FxRate")).first.getString(0)

Answer 2

Here是您需要使用的功能

像这样使用：

fxRatesDF.first().FxRate

Answer 3

也许是这样：

fxRatesDF.take(1)[0][1]

或

fxRatesDF.collect()[0][1]

或

fxRatesDF.first()[1]

Answer 4

我知道这是一篇旧帖子，但我让它以这种方式工作fxRatesDF.first()[0]

Answer 5

您可以尝试以下方法：

fxRatesDF.select("FxRate").rdd.map{case Row(i:Int)=> i}.first()

Answer 6

应该如此简单：

display(fxRatesDF.select($"FxRate").limit(1))

Answer 7

只需一行就可以解决这个问题。

fxRates.first()(1)

或

一行有两个单词

fxRates.first().getString(1)

Answer 8

一种简单的方法是使用索引选择行和列。输入数据框：

+-----+
|count|
+-----+
|    0|
+-----+

代码：

count = df.collect()[0][0]
print(count)
if count == 0:
    print("First row and First column value is 0")

输出：

0
First row and First column value is 0

从spark.sql.Row获取第一个值

8 个答案: