Question

我有一个数据框，即resultDf，如下所示

+---------------+-------------------+--------------------+-------------------+-------------------+--------------+-----------------------+----------------------+
|model_family_id|classification_type|classification_value|benchmark_type_code|          data_date|data_item_code|data_item_value_numeric|data_item_value_string|
+---------------+-------------------+--------------------+-------------------+-------------------+--------------+-----------------------+----------------------+
|              1|            COUNTRY|                 AGO|               MEAN|2018-03-31 00:00:00|   CREDITSCORE|                     15|                     b|
|              1|            COUNTRY|                 AGO|            OBS_CNT|2018-03-31 00:00:00|   CREDITSCORE|                      4|                     b|
|              1|            COUNTRY|                 AGO|         OBS_CNT_CA|2018-03-31 00:00:00|   CREDITSCORE|                      4|                  null|
|              1|            COUNTRY|                 AGO|       PERCENTILE_0|2018-03-31 00:00:00|   CREDITSCORE|                     15|                     b|
|              1|            COUNTRY|                 AGO|      PERCENTILE_10|2018-03-31 00:00:00|   CREDITSCORE|                     15|                     b|
|              1|            COUNTRY|                 AGO|     PERCENTILE_100|2018-03-31 00:00:00|   CREDITSCORE|                     15|                     b|
|              1|            COUNTRY|                 AGO|      PERCENTILE_25|2018-03-31 00:00:00|   CREDITSCORE|                     15|                     b|
|              1|            COUNTRY|                 AGO|      PERCENTILE_50|2018-03-31 00:00:00|   CREDITSCORE|                     15|                     b|
|              1|            COUNTRY|                 AGO|      PERCENTILE_75|2018-03-31 00:00:00|   CREDITSCORE|                     15|                     b|
|              1|            COUNTRY|                 AGO|      PERCENTILE_90|2018-03-31 00:00:00|   CREDITSCORE|                     15|                     b|
+---------------+-------------------+--------------------+-------------------+-------------------+--------------+-----------------------+----------------------+

我根据“ benchmark_type_code”列来旋转数据表，需要实现下面的业务逻辑

如果（data_item_code）是“ SCORE”或“ PG_SCORE” ====>选择data_item_value_string作为值其他 ==>选择data_item_value_numeric作为值

为此，我编写了以下代码


   val pivot_resultDf =  resultDf.groupBy("model_family_id","classification_type","classification_value" ,"benchmark_type_code","data_date")
                .pivot("benchmark_type_code")
                .agg( first( 
                        when( col("data_item_code").===("SCORE"),  col("data_item_value_numeric"))
                             .otherwise(col("data_item_value_string"))
                    ) )

但是当条件出现时，我在agg函数中遇到错误


java.lang.AssertionError: assertion failed: unsafe symbol Unstable (child of <none>) in runtime reflection universe
    at scala.reflect.internal.Symbols$Symbol.<init>(Symbols.scala:205)
    at scala.reflect.internal.Symbols$TypeSymbol.<init>(Symbols.scala:3030)
    at scala.reflect.internal.Symbols$Symbol.newStubSymbol(Symbols.scala:521)
    at scala.reflect.internal.pickling.UnPickler$Scan.readExtSymbol$1(UnPickler.scala:258)
    at scala.reflect.internal.pickling.UnPickler$Scan.readSymbol(UnPickler.scala:286)
    at scala.reflect.runtime.JavaMirrors$JavaMirror.unpickleClass(JavaMirrors.scala:619)
    at scala.reflect.runtime.SymbolLoaders$TopClassCompleter$$anonfun$complete$1.apply$mcV$sp(SymbolLoaders.scala:28)
    at scala.reflect.runtime.SymbolLoaders$TopClassCompleter$$anonfun$complete$1.apply(SymbolLoaders.scala:25)
    at scala.reflect.runtime.SymbolLoaders$TopClassCompleter$$anonfun$complete$1.apply(SymbolLoaders.scala:25)
    at scala.reflect.internal.SymbolTable.slowButSafeEnteringPhaseNotLaterThan(SymbolTable.scala:263)
    at scala.reflect.runtime.SymbolLoaders$TopClassCompleter.complete(SymbolLoaders.scala:25)
    at scala.reflect.internal.Symbols$Symbol.info(Symbols.scala:1535)
    at org.apache.spark.sql.catalyst.expressions.Literal$.create(literals.scala:158)
    at org.apache.spark.sql.functions$.typedLit(functions.scala:113)
    at org.apache.spark.sql.functions$.lit(functions.scala:96)
    at org.apache.spark.sql.Column.$eq$eq$eq(Column.scala:262)

我在这里做错了什么？如何解决这个问题？

Answer 1

我不确定为什么会收到断言错误，但是我能够成功获得结果。通常，断言错误是语法错误。请检查行尾并尝试在spark shell上执行以查看真正的间隙在哪里。找到显示我能够获得期望结果的屏幕截图。

Answer 2

这正在工作

.agg（first（ when（col（“ data”）。isin（“ x”，“ a”，“ y”，“ z”）， when（col（“ code”）。isin（“ aa”，“ bb”），col（“ numeric”））。otherwise（col（“ string”））） .otherwise（col（“ numeric”）））

火花数据帧透视引发AssertionError：断言失败：不安全符号不稳定

2 个答案: