代碼場景：

1）設定的幾種數據場景，遍歷所有場景：依次統計滿足每種場景條件下的數據，并把統計結果存入hive；

2）已有代碼如下：

case class IndoorOTTCalibrateBuildingVecotrLegend(oid: Int, minHeight: Int, maxHeight: Int, minGridIDCount: Int, maxGridIDCount: Int, heightType: Int) extends Serializable // 實例化建筑物區間段：按照柵格的個數（面積）、樓的高度（商場等場景）來劃分場景val buildingHeightLegends = List(IndoorOTTCalibrateBuildingVecotrLegend(1, 1, 30, 1, 21, BuildingCalibrateHeightType.HeightType1.toString.toInt),IndoorOTTCalibrateBuildingVecotrLegend(2, 1, 30, 21, 45, BuildingCalibrateHeightType.HeightType2.toString.toInt),IndoorOTTCalibrateBuildingVecotrLegend(3, 1, 30, 45, 100, BuildingCalibrateHeightType.HeightType3.toString.toInt),IndoorOTTCalibrateBuildingVecotrLegend(4, 30, 50, 1, 21, BuildingCalibrateHeightType.HeightType4.toString.toInt),IndoorOTTCalibrateBuildingVecotrLegend(5, 30, 50, 21, 45, BuildingCalibrateHeightType.HeightType5.toString.toInt),IndoorOTTCalibrateBuildingVecotrLegend(6, 30, 50, 45, 100, BuildingCalibrateHeightType.HeightType6.toString.toInt),IndoorOTTCalibrateBuildingVecotrLegend(7, 50, 5000, 1, 100, BuildingCalibrateHeightType.HeightType7.toString.toInt))spark.sparkContext.parallelize(buildingHeightLegends).collect().foreach(buildingHeightLegend => {generateSampleBySenceType(spark, p_city, p_hour_start, p_hour_end, p_fpb_day, p_day_sample, linkLossCalibrateParameter, buildingHeightLegend)})

備注：

在generateSampleBySenceType()函數內部包含有:

spark.sql(s"""
|xxx |where t10.heihgt>=${buildingHieghtLegend.MinHeight} and t10.height<${buildingHieghtLegend.MaxHeight} |and t10.gridcount<=${buildingHieghtLegend.MinGridIDCount} and t10.gridcount>${buildingHieghtLegend.MaxGridIDCount}
|""".stripMargin)

如果把代碼修改：

val buildingHeightLegends_df = spark.sqlContext.createDataFrame(buildingHeightLegends)buildingHeightLegends_df.createOrReplaceTempView("temp_buildingheightlegends")sql(s"""|select * from temp_buildingheightlegends""".stripMargin).repartition(buildingHeightLegends.length).foreachPartition(rows => {for (row <- rows) {val buildingHeightLegend = new IndoorOTTCalibrateBuildingVecotrLegend(row.getAs[Int]("oid"),row.getAs[Int]("minheight"),row.getAs[Int]("maxheight"),row.getAs[Int]("mingrididcount"),row.getAs[Int]("maxgrididcount"),row.getAs[Int]("heighttype"))generateSampleBySenceType(spark, p_city, p_hour_start, p_hour_end, p_fpb_day, p_day_sample, linkLossCalibrateParameter, buildingHeightLegend)}})

則會提示：generateSampleBySenceType()內部sql代碼位置拋出SparkSession為NULL的異常。

修改方案：

把buildingHeightLegends注冊為臨時表temp_buildingHeightLegends，去掉外層的foreach，之后在generateSampleBySenceType()內部把temp_buildingHeightLegends與其他結果集合進行cross join：

測試代碼如下：

-- 場景表 CREATE TABLE [dbo].[test_senceitems]([sencetype] [int] NULL,[minheight] [int] NULL,[maxheight] [int] NULL,[mingridcount] [int] NULL,[maxgridcount] [int] NULL ) INSERT [dbo].[test_senceitems] ([sencetype], [minheight], [maxheight], [mingridcount], [maxgridcount]) VALUES (1, 1, 30, 1, 21) INSERT [dbo].[test_senceitems] ([sencetype], [minheight], [maxheight], [mingridcount], [maxgridcount]) VALUES (2, 1, 30, 21, 45) INSERT [dbo].[test_senceitems] ([sencetype], [minheight], [maxheight], [mingridcount], [maxgridcount]) VALUES (3, 1, 30, 45, 100) INSERT [dbo].[test_senceitems] ([sencetype], [minheight], [maxheight], [mingridcount], [maxgridcount]) VALUES (4, 30, 50, 1, 21) INSERT [dbo].[test_senceitems] ([sencetype], [minheight], [maxheight], [mingridcount], [maxgridcount]) VALUES (5, 30, 50, 21, 45) INSERT [dbo].[test_senceitems] ([sencetype], [minheight], [maxheight], [mingridcount], [maxgridcount]) VALUES (6, 30, 50, 45, 100) INSERT [dbo].[test_senceitems] ([sencetype], [minheight], [maxheight], [mingridcount], [maxgridcount]) VALUES (7, 50, 5000, 1, 100)-- 業務過濾統計表 CREATE TABLE [dbo].[test_grid]([gridid] [nvarchar](50) NULL,[height] [int] NULL,[gridcount] [int] NULL ) INSERT [dbo].[test_grid] ([gridid], [height], [gridcount]) VALUES (N'g1', 8, 23) INSERT [dbo].[test_grid] ([gridid], [height], [gridcount]) VALUES (N'g2', 3, 87) INSERT [dbo].[test_grid] ([gridid], [height], [gridcount]) VALUES (N'g3', 4, 34) INSERT [dbo].[test_grid] ([gridid], [height], [gridcount]) VALUES (N'g4', 30, 54) INSERT [dbo].[test_grid] ([gridid], [height], [gridcount]) VALUES (N'g5', 32, 32) INSERT [dbo].[test_grid] ([gridid], [height], [gridcount]) VALUES (N'g6', 32, 20) INSERT [dbo].[test_grid] ([gridid], [height], [gridcount]) VALUES (N'g7', 120, 34) INSERT [dbo].[test_grid] ([gridid], [height], [gridcount]) VALUES (N'g8', 89, 54) INSERT [dbo].[test_grid] ([gridid], [height], [gridcount]) VALUES (N'g9', 9, 16)

替換generateSampleBySenceType()內部sql(s"""|""".stripMargin)代碼類似如下：

select t10.*,t11.* from test_grid t10 cross join test_senceitems t11 where t10.height>=t11.minheight and t10.height<t11.maxheight and t10.gridcount>=t11.mingridcount and t10.gridcount<t11.maxgridcount

?

轉載于:https://www.cnblogs.com/yy3b2007com/p/8505152.html

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