Can anyone please tell me the process of incremental updates in Hive.
Actually i would like to understand with the help of Hive, how do we manage the master data table.
If everyday there are new set of records coming to get inserted into hive table.
In the new set of records there could be new keys, there could be existing keys which need an update.
I found some information at the link.
Can any one please guide me.
Related
I'm trying to update a record based on ID field in Hive table using informtica cloud data integration. But the problem is Instead of updating the existing record it is creating new record. Can anyone please suggest better approach
I have a table created in production with incorrect data.My rec_srt_dt and rec_end_dt columns have been loaded wrongly. rec_srt_dt is sys_dt and now I have modified the query to load the data properly. My question is how do I have to handle the existing data present in production table and how to add new changes to that data?
My source table is oracle, Using Spark for the transformations and the target table is in AWS.
Kindly help me in this.
I am using a Google Sheet as the source of a table in Big Query. Since I am unable to rename fieldnames in the schema of an existing table I deleted the table and attempted to re-create it after amending the column names in the source Google Sheet. I need to keep the table name the same as I already have analysis files connecting to the table, however when I create the new table as ask Big Query to auto-detect the schema it uses the schema of the previous table. Even if I enter the new schema as text when creating the table it ignores what I enter and use the schema from the old table.
Any ideas how I get Big Query to detect the new schema from the Google Sheet whilst using the same table name as the deleted table?
Thanks in advance!
After trying this multiple times and it not working - with several tables - randomly it worked and let me create a table with the new scheme (manually). Not sure why this didn't work before as I'm pretty sure I didn't do anything differently. If anyone has any insight on what might have caused the initial errors I'd love to hear it for future reference but my current problem is solved.
I have taken over a project with minimal knowledge on how to use Azure Data Factory so need some help. The data factory is copying data from one postgres sql server over to my azure sql server. It is running 3 times a day and inserts new rows perfectly. But when data has changed in postgres it does not update the row as needed in the sink database. Can anyone point me in the right direction?
Since the source are on-premise, you can't use data flow. It means that the tutorial #Mark kromer provided for you doesn't works.
Per my experience in Copy active, we only can copy(insert) the data to sink table, won't update it. I'm afraid to say we can't update rows with copy active.
I'm using Spark Streaming and Hive. I want to insert or update data into exist table in hive using SparkSQL. But, I don't know check whether data existed. Please suggest me this question!