Add Column in a Spark Dataframe ,based on a parametric sql query dependent on values of some fields of the dataframe - sql

Question

I have several Spark Dataframes(we can call them Table a, table b etc).
I want to add a column just to table a, based on a result of a query to one of the other tables, but this table will change every time based on a value of one of the fields of table a. So this query should be parametric.
Below I show an example to make the problem clear:
Every table has the column OID and a column TableName with the name of the current table, plus other columns.
This is the fixed query to be performed on Tab A to add new column:
Select $ColumnName from $TableName where OID=$oids
Tab A
| oids|TableName |ColumnName | other fields|New Column: ValueOidDb
================================================================
| 2 | Book | Title | x |result query:harry potter
| 8 | Book | Isbn | y |result query: 556
| 1 | Author | Name | z |result query:Tolkien
| 4 | Category |Description| b |result query: Commedy
Tab Book
| OID |TableName |Title |Isbn |other fields|
================================================================
| 2 | Book |harry potter| 123 | x |
| 8 | Book | hobbit | 556 | y |
| 21 | Book | etc | 8942 | z |
| 5 | Book | etc2 | 984 | b |
Tab Author
| OID |TableName |Name |nationality |other fields|
================================================================
| 5 | Author |J.Rowling | eng | x |
| 2 | Author |Geor. Martin| us | y |
| 1 | Author | Tolkien | eng | z |
| 13 | Author | Dan Brown | us | b |
| OID | TableName |Description |
=====================================
| 12 | Category | Fantasy |
| 4 | Category | Commedy |
| 9 | Category | Thriller |
| 7 | Category | Action |
I tried with this udf
def setValueOid = (oid: Int,TableName: String, TableColumn: String) => {
try{
sqlContext.sql(s"Select $currTableColumn from $currTableName where OID = $curroid ").first().toString()
}
catch{
case x: java.lang.NullPointerException => "error"
}
}
sqlContext.udf.register("setValueOid", setValueOid)
val FinalRtxf = sqlContext.sql("SELECT all the column of TAB A ,"
+ " setValueOid(oid, Table,AttributeDatabaseColumn ) as ValueOidDb"
+ " FROM TAB A")
I put the code in a try catch because otherwise it gives me a nullpointerexception, but it doesn't work, because it always returns a "problem".
If I try this function without a sql query by just passing some manual parameters it works perfectly:
val try=setValueOid(8,"BOOK","ISBN")
try: String = [0977326403 ] FINISHED
Took 4 sec. Last updated by anonymous at November 20 2016, 3:29:28 AM.
I read here that is not possible to make a query inside a udf
Trying to execute a spark sql query from a UDF
So how can I solve my problem? I don't know how to make a parametric join. I tried this:
%sql
Select all attributes TAB A,
FROM TAB A as a
join (Select $AttributeDatabaseColumn ,TableName from $Table where OID=$oid) as b
on a.Table=b.TableName
but it gave me this exception:
org.apache.spark.sql.AnalysisException: cannot recognize input near '$' 'AttributeDatabaseColumn' ',' in select clause; line 3 pos 1 at org.apache.spark.sql.hive.HiveQl$.createPlan(HiveQl.scala:318)
at org.apache.spark.sql.hive.ExtendedHiveQlParser$$anonfun$hiveQl$1.apply(ExtendedHiveQlParser.scala:41)
at org.apache.spark.sql.hive.ExtendedHiveQlParser$$anonfun$hiveQl$1.apply(ExtendedHiveQlParser.scala:40)

Answer 1

One option:
transform each Book, Author, Category to a form:
root
|-- oid: integer (nullable = false)
|-- tableName: string (nullable = true)
|-- properties: map (nullable = true)
| |-- key: string
| |-- value: string (valueContainsNull = true)
For example first record in Book:
val book = Seq((2L, "Book",
Map("title" -> "harry potter", "Isbn" -> "123", "other field" -> "x")
)).toDF("oid", "title", "properties")
+---+---------+---------------------------------------------------------+
|oid|tableName|properties |
+---+---------+---------------------------------------------------------+
|2 |Book |Map(title -> harry potter, Isbn -> 123, other field -> x)|
+---+---------+---------------------------------------------------------+
union Book, Author, Category as properties.
val properties = book.union(author).union(category)
join with base table:
val comb = properties.join(table, Seq($"oid", $"tableName"))
use case when ... based on tableName to add new column from properties field.