pyspark add min value to back to dataframe - python-3.x

Question

I'm trying to find the min date in a column 'dateclosed' in a pyspark dataframe. I then want to add a column to my original dataframe, so that every record would have the minimum date 'Open_Date'. This really seems like it shouldn't be that hard, but I keep getting errors. I've also tried using "join" and creating a field with only one value in both dataframes and trying to join them on that, but again I just get errors. Does anyone have a solution?
Code:
tst2_df=tst_df[['dateclosed']].agg({'dateclosed':'min'})\
.withColumnRenamed('min(dateclosed)','Open_Date')
tst_df.withColumn('Open_Date',lit(tst2_df[['Open_Date']].collect()[0])).show()
errors:
An error occurred while calling z:org.apache.spark.sql.functions.lit.
: java.lang.RuntimeException: Unsupported literal type class java.util.ArrayList [2017-01-01]
at org.apache.spark.sql.catalyst.expressions.Literal$.apply(literals.scala:78)
at org.apache.spark.sql.catalyst.expressions.Literal$$anonfun$create$2.apply(literals.scala:164)
at org.apache.spark.sql.catalyst.expressions.Literal$$anonfun$create$2.apply(literals.scala:164)
at scala.util.Try.getOrElse(Try.scala:79)
at org.apache.spark.sql.catalyst.expressions.Literal$.create(literals.scala:163)
at org.apache.spark.sql.functions$.typedLit(functions.scala:127)
at org.apache.spark.sql.functions$.lit(functions.scala:110)
at org.apache.spark.sql.functions.lit(functions.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Traceback (most recent call last):
File "/mnt/yarn/usercache/livy/appcache/application_1571940153295_0002/container_1571940153295_0002_01_000001/pyspark.zip/pyspark/sql/functions.py", line 44, in _
jc = getattr(sc._jvm.functions, name)(col._jc if isinstance(col, Column) else col)
File "/mnt/yarn/usercache/livy/appcache/application_1571940153295_0002/container_1571940153295_0002_01_000001/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
answer, self.gateway_client, self.target_id, self.name)
File "/mnt/yarn/usercache/livy/appcache/application_1571940153295_0002/container_1571940153295_0002_01_000001/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/mnt/yarn/usercache/livy/appcache/application_1571940153295_0002/container_1571940153295_0002_01_000001/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.sql.functions.lit.
: java.lang.RuntimeException: Unsupported literal type class java.util.ArrayList [2017-01-01]
at org.apache.spark.sql.catalyst.expressions.Literal$.apply(literals.scala:78)
at org.apache.spark.sql.catalyst.expressions.Literal$$anonfun$create$2.apply(literals.scala:164)
at org.apache.spark.sql.catalyst.expressions.Literal$$anonfun$create$2.apply(literals.scala:164)
at scala.util.Try.getOrElse(Try.scala:79)
at org.apache.spark.sql.catalyst.expressions.Literal$.create(literals.scala:163)
at org.apache.spark.sql.functions$.typedLit(functions.scala:127)
at org.apache.spark.sql.functions$.lit(functions.scala:110)
at org.apache.spark.sql.functions.lit(functions.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Update:
This hack worked, thanks for the tip Pault
tst_df2=tst_df.withColumn('BS',lit('a'))
w = Window.partitionBy('BS')
tst_df2.select('BS','dateclosed', min('dateclosed').over(w).alias('n')).show()

Answer 1

tst_df2=tst_df.withColumn('BS',lit('a'))
w = Window.partitionBy('BS')
tst_df2.select('BS','dateclosed', min('dateclosed').over(w).alias('n')).show()