最近工作中把一些sql.sh脚本执行hive的语句升级为spark2.1版本，其中遇到将case when 替换为scala操作df的方式实现的问题：
代码数据：
scala> import org.apache.spark.sql.functions._ import org.apache.spark.sql.functions._ scala> import spark.implicits._ import spark.implicits._ scala> case class fpb_servercls(gridid: String, height: Int, objectid: Int, rsrp: Double, calibrategridid: Int, calibartetype: String) defined class fpb_servercls scala> | val fpb_server_test = List( | fpb_servercls("grid1", 0, 888888, -88, 53, null), | fpb_servercls("grid1", 5, 888888, -99, 53, null), | fpb_servercls("grid2", 0, 333333, -78, 53, null), | fpb_servercls("grid4", 0, 444444, -78, 53, null) | ).toDF fpb_server_test: org.apache.spark.sql.DataFrame = [gridid: string, height: int ... 4 more fields] scala> val sampe_data_test = List( | fpb_servercls("grid1", 0, 888888, -78, 53, "HOMEWIFI"), | fpb_servercls("grid1", 5, 999999, -89, 53, null), | fpb_servercls("grid2", 0, 333333, -87, 53, null) | ).toDF sampe_data_test: org.apache.spark.sql.DataFrame = [gridid: string, height: int ... 4 more fields]
错误代码：
scala> val temp_result = fpb_server_test.alias("fpb").join(sampe_data_test.alias("sample"),
| fpb_server_test("gridid") === sampe_data_test("gridid")
| && fpb_server_test("height") === sampe_data_test("height")
| && fpb_server_test("objectid") === sampe_data_test("objectid"), "left_outer")
| .select(
| fpb_server_test("gridid"),
| fpb_server_test("height"),
| fpb_server_test("objectid"),
| when(sampe_data_test("gridid") === lit(null), fpb_server_test("rsrp")).otherwise(sampe_data_test("rsrp")).alias("rsrp"),
| fpb_server_test("calibrategridid"),
| when(sampe_data_test("gridid") === lit(null), fpb_server_test("calibartetype")).otherwise(sampe_data_test("calibartetype")).alias("f_calibartetype")
| )
temp_result: org.apache.spark.sql.DataFrame = [gridid: string, height: int ... 4 more fields]
scala> temp_result.show
+------+------+--------+-----+---------------+---------------+
|gridid|height|objectid| rsrp|calibrategridid|f_calibartetype|
+------+------+--------+-----+---------------+---------------+
| grid1| 0| 888888|-78.0| 53| HOMEWIFI|
| grid1| 5| 888888| null| 53| null|
| grid2| 0| 333333|-87.0| 53| null|
| grid4| 0| 444444| null| 53| null|
+------+------+--------+-----+---------------+---------------+
错误的愿意就是这里的判定是否为空的地方。
正确用法：
scala> val temp_result = fpb_server_test.alias("fpb").join(sampe_data_test.alias("sample"),
| fpb_server_test("gridid") === sampe_data_test("gridid")
| && fpb_server_test("height") === sampe_data_test("height")
| && fpb_server_test("objectid") === sampe_data_test("objectid"), "left_outer")
| .select(
| fpb_server_test("gridid"),
| fpb_server_test("height"),
| fpb_server_test("objectid"),
| when(sampe_data_test("gridid").isNull, fpb_server_test("rsrp")).otherwise(sampe_data_test("rsrp")).alias("rsrp"),
| fpb_server_test("calibrategridid"),
| when(sampe_data_test("gridid").isNull, fpb_server_test("calibartetype")).otherwise(sampe_data_test("calibartetype")).alias("f_calibartetype")
| )
temp_result: org.apache.spark.sql.DataFrame = [gridid: string, height: int ... 4 more fields]
scala> temp_result.show
+------+------+--------+-----+---------------+---------------+
|gridid|height|objectid| rsrp|calibrategridid|f_calibartetype|
+------+------+--------+-----+---------------+---------------+
| grid1| 0| 888888|-78.0| 53| HOMEWIFI|
| grid1| 5| 888888|-99.0| 53| null|
| grid2| 0| 333333|-87.0| 53| null|
| grid4| 0| 444444|-78.0| 53| null|
+------+------+--------+-----+---------------+---------------+
疑问代码，如下代码在spark-shell中执行没有问题，但是使用spark-submit提交脚本后就提示错误：
scala> val temp_result = fpb_server_test.alias("fpb").join(sampe_data_test.alias("sample"),
| fpb_server_test("gridid") === sampe_data_test("gridid")
| && fpb_server_test("height") === sampe_data_test("height")
| && fpb_server_test("objectid") === sampe_data_test("objectid"), "left_outer")
| .selectExpr("fpb.gridid", "fpb.height", "fpb.objectid",
| "(case when sample.gridid is null then fpb.rsrp else sample.rsrp end) as rsrp",
| "fpb.calibrategridid",
| "(case when sample.gridid is null then fpb.calibartetype else sample.calibartetype end) as calibartetype")
temp_result: org.apache.spark.sql.DataFrame = [gridid: string, height: int ... 4 more fields]
scala> temp_result.show
+------+------+--------+-----+---------------+-------------+
|gridid|height|objectid| rsrp|calibrategridid|calibartetype|
+------+------+--------+-----+---------------+-------------+
| grid1| 0| 888888|-78.0| 53| HOMEWIFI|
| grid1| 5| 888888|-99.0| 53| null|
| grid2| 0| 333333|-87.0| 53| null|
| grid4| 0| 444444|-78.0| 53| null|
+------+------+--------+-----+---------------+-------------+
