Try the same union with a dataframe without the arrays types. Could be something strange there like ordering or so.
Jorge Machado > On 4 Jun 2018, at 10:17, Pranav Agrawal <pranav.mn...@gmail.com> wrote: > > schema is exactly the same, not sure why it is failing though. > > root > |-- booking_id: integer (nullable = true) > |-- booking_rooms_room_category_id: integer (nullable = true) > |-- booking_rooms_room_id: integer (nullable = true) > |-- booking_source: integer (nullable = true) > |-- booking_status: integer (nullable = true) > |-- cancellation_reason: integer (nullable = true) > |-- checkin: string (nullable = true) > |-- checkout: string (nullable = true) > |-- city_id: integer (nullable = true) > |-- cluster_id: integer (nullable = true) > |-- company_id: integer (nullable = true) > |-- created_at: string (nullable = true) > |-- discount: integer (nullable = true) > |-- feedback_created_at: string (nullable = true) > |-- feedback_id: integer (nullable = true) > |-- hotel_id: integer (nullable = true) > |-- hub_id: integer (nullable = true) > |-- month: integer (nullable = true) > |-- no_show_reason: integer (nullable = true) > |-- oyo_rooms: integer (nullable = true) > |-- selling_amount: integer (nullable = true) > |-- shifting: array (nullable = true) > | |-- element: struct (containsNull = true) > | | |-- id: integer (nullable = true) > | | |-- booking_id: integer (nullable = true) > | | |-- shifting_status: integer (nullable = true) > | | |-- shifting_reason: integer (nullable = true) > | | |-- shifting_metadata: integer (nullable = true) > |-- suggest_oyo: integer (nullable = true) > |-- tickets: array (nullable = true) > | |-- element: struct (containsNull = true) > | | |-- ticket_source: integer (nullable = true) > | | |-- ticket_status: string (nullable = true) > | | |-- ticket_instance_source: integer (nullable = true) > | | |-- ticket_category: string (nullable = true) > |-- updated_at: timestamp (nullable = true) > |-- year: integer (nullable = true) > |-- zone_id: integer (nullable = true) > > root > |-- booking_id: integer (nullable = true) > |-- booking_rooms_room_category_id: integer (nullable = true) > |-- booking_rooms_room_id: integer (nullable = true) > |-- booking_source: integer (nullable = true) > |-- booking_status: integer (nullable = true) > |-- cancellation_reason: integer (nullable = true) > |-- checkin: string (nullable = true) > |-- checkout: string (nullable = true) > |-- city_id: integer (nullable = true) > |-- cluster_id: integer (nullable = true) > |-- company_id: integer (nullable = true) > |-- created_at: string (nullable = true) > |-- discount: integer (nullable = true) > |-- feedback_created_at: string (nullable = true) > |-- feedback_id: integer (nullable = true) > |-- hotel_id: integer (nullable = true) > |-- hub_id: integer (nullable = true) > |-- month: integer (nullable = true) > |-- no_show_reason: integer (nullable = true) > |-- oyo_rooms: integer (nullable = true) > |-- selling_amount: integer (nullable = true) > |-- shifting: array (nullable = true) > | |-- element: struct (containsNull = true) > | | |-- id: integer (nullable = true) > | | |-- booking_id: integer (nullable = true) > | | |-- shifting_status: integer (nullable = true) > | | |-- shifting_reason: integer (nullable = true) > | | |-- shifting_metadata: integer (nullable = true) > |-- suggest_oyo: integer (nullable = true) > |-- tickets: array (nullable = true) > | |-- element: struct (containsNull = true) > | | |-- ticket_source: integer (nullable = true) > | | |-- ticket_status: string (nullable = true) > | | |-- ticket_instance_source: integer (nullable = true) > | | |-- ticket_category: string (nullable = true) > |-- updated_at: timestamp (nullable = false) > |-- year: integer (nullable = true) > |-- zone_id: integer (nullable = true) > > On Sun, Jun 3, 2018 at 8:05 PM, Alessandro Solimando > <alessandro.solima...@gmail.com <mailto:alessandro.solima...@gmail.com>> > wrote: > Hi Pranav, > I don´t have an answer to your issue, but what I generally do in this cases > is to first try to simplify it to a point where it is easier to check what´s > going on, and then adding back ¨pieces¨ one by one until I spot the error. > > In your case I can suggest to: > > 1) project the dataset to the problematic column only (column 21 from your > log) > 2) use explode function to have one element of the array per line > 3) flatten the struct > > At each step use printSchema() to double check if the types are as you expect > them to be, and if they are the same for both datasets. > > Best regards, > Alessandro > > On 2 June 2018 at 19:48, Pranav Agrawal <pranav.mn...@gmail.com > <mailto:pranav.mn...@gmail.com>> wrote: > can't get around this error when performing union of two datasets > (ds1.union(ds2)) having complex data type (struct, list), > > 18/06/02 15:12:00 INFO ApplicationMaster: Final app status: FAILED, exitCode: > 15, (reason: User class threw exception: > org.apache.spark.sql.AnalysisException: Union can only be performed on tables > with the compatible column types. > array<struct<id:int,booking_id:int,shifting_status:int,shifting_reason:int,shifting_metadata:string>> > <> > array<struct<id:int,booking_id:int,shifting_status:int,shifting_reason:int,shifting_metadata:string>> > at the 21th column of the second table;; > > As far as I can tell, they are the same. What am I doing wrong? Any help / > workaround appreciated! > > spark version: 2.2.1 > > Thanks, > Pranav > >
