Spark DataFrame SQL count * with where子句给出了错误的结果？

Question

计算不正确的结果。

+--------+
|count(1)|
+--------+
|       0| // Should not be zero
+--------+

这是相关代码：

val customSchema = StructType(Array(
    StructField("_c0", StringType, true),
    StructField("Birth_Country", StringType, true),
    StructField("Email", StringType, true),
    StructField("First_Name", StringType, true),
    StructField("Job", StringType, true),
    StructField("Last_name", StringType, true),
    StructField("SSN", StringType, true),
    StructField("Loan_Approved", StringType, true),
    StructField("Income", DoubleType, true)))
    StructField("bytes_served", DoubleType, true)))

val df = spark.read.format("csv").option("header", `"true")
  //.load("examples/src/main/resources/Fake_data.csv")
  .schema(customSchema)
  .load("examples/src/main/resources/Fake_data.csv")

df.show()

// System.exit(1)
df.select("Birth_Country", "Email","First_Name","Job","Last_name","Loan_Approved","SSN").show()

df.createOrReplaceTempView("people")

val sqlDF2 = spark.sql("SELECT Birth_Country, count(Birth_Country) as bm FROM people group by Birth_Country");`

sqlDF2.createOrReplaceTempView("BC")

val ans_1 = spark.sql("select Birth_Country, bm as count from BC where bm = (select max(bm) from BC)")

val ans_2 = spark.sql("select mean(Income) from people where Birth_Country='United States of America'")

val ans_4=spark.sql("select count(*) from people where  Income > 1000.00   ")

ans_1.show 
ans_2.show 
ans_4.show 

数据就像......第一个字段为空

Birth_Country   Email   First_Name  Income  Job Last_name   Loan_Approved   SSN
----------
0   Bosnia and Herzegovina  emily15@whitehead.com   Melissa 109957.00   Telecommunications researcher   Miranda FALSE   129-41-7773
1   Belgium ronald87@yahoo.com  Curtis  301884.00   Animal nutritionist Garrett TRUE    212-74-3976
2   United Kingdom  hannah29@gmail.com  Connor  341584.00   English as a foreign language teacher   Steele  FALSE   024-35-3834
3   Kiribati    derrick59@hotmail.com   Adam    448293.00   Surveyor, commercial/residential    Newman  FALSE   157-82-4486