I have data in my hive table which was partitioned by date. As one day data is huge, I want to further divide this data into 4 parts. so that I want to read each part and process the data.
For making one day data into 4 parts, can we use bucketing on same date field and give 4 buckets to make 4 parts?
create table state_part(District string,Enrolments string) PARTITIONED BY(enrolled_date string) CLUSTERED BY (enrolled_date) into 4 buckets;
I am new to hive and could some one help me to brake this one day data into 4 parts and then read one part of data at a time.
Really appreciate your help.
Thanks,
Babu
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I have a couple of years of data on a big query partitioned table by day. I want to replace the data of just the last 30 days; however, when I use the create or replace table function on bigquery, it replaces the entire table with just the new dates partitions. Is there any way to update only those partitions without losing the previous data?
I have a table records with structure
userId
messageId
message
timestamp
This table grows pretty large so I want to split it into two
records which will have only data for the last 30 days
and records_history which will have all the data, so most of the queries will hit only records table.
What is the best way to achieve this using Oracle? Writing a trigger or something else?
My question is about table partitioning in SQL Server 2008.
I have a program that loads data into a table every 10 mins or so. Approx 40 million rows per day.
The data is bcp'ed into the table and needs to be able to be loaded very quickly.
I would like to partition this table based on the date the data is inserted into the table. Each partition would contain the data loaded in one particular day.
The table should hold the last 50 days of data, so every night I need to drop any partitions older than 50 days.
I would like to have a process that aggregates data loaded into the current partition every hour into some aggregation tables. The summary will only ever run on the latest partition (since all other partitions will already be summarised) so it is important it is partitioned on insert_date.
Generally when querying the data, the insert date is specified (or multiple insert dates). The detailed data is queried by drilling down from the summarised data and as this is summarised based on insert date, the insert date is always specified when querying the detailed data in the partitioned table.
Can I create a default column in the table "Insert_date" that gets a value of Getdate() and then partition on this somehow?
OR
I can create a column in the table "insert_date" and put a hard coded value of today's date.
What would the partition function look like?
Would seperate tables and a partitioned view be better suited?
I have tried both, and even though I think partition tables are cooler. But after trying to teach how to maintain the code afterwards it just wasten't justified. In that scenario we used a hard coded field date field that was in the insert statement.
Now I use different tables ( 31 days / 31 tables ) + aggrigation table and there is an ugly union all query that joins togeather the monthly data.
Advantage. Super timple sql, and simple c# code for bcp and nobody has complained about complexity.
But if you have the infrastructure and a gaggle of .net / sql gurus I would choose the partitioning strategy.