I have a legacy application currently running on Oracle 11g, a table which has 3 million data from the year of 2003 to to 2022 and data continuously growing. This table has 43 columns.
Because of this huge data, entire application is running slow.
The primary key of this table is used in most of the joins. all the columns are storing numbers except the creation date.
I was thinking of partitioning the table by year or every 6 months or every quarter.
As the data is growing everyday, I should be able to create a partition automatically for upcoming years.
which would be the better way to partition this table.?
how do I do partition on existing non partitioned table.?
Kindly provide some examples I can refer.
Looking for best advises.
Related
We have a primary table that is Range partitioned by date with a 1-month interval. It's also a list sub-partitioned with 4 distinct values. So essentially it is one month partition having 4 sub-partitions.
Database: Oracle 19c
I need advice on how to effectively move the partition/sub-partition data from active schema to historical schema in another database.
Also, there are about 30 tables that are referenced partitioned on the primary table for which the data needs to be moved as well. Overall I'm looking to move about 2500 subpartitions
I'm not sure if an exchange partition would be the right approach in this scenario?
TIA
You could use exchange to get the data rapidly out of your active table, but you would still then to send that table over the wire to the remote history database to load it in.
In which case, using "exchange" probably is just adding more steps to the process for little gain. (There are still potential uses here depending on how you want to handle indexing etc).
But simplest is perhaps just transferring the data over, assuming a common structure between the two tables, ie
insert /*+ APPEND */ into history_table#remote_db
select * from active_table partition ( myparname )
I can't remember if partition naming syntax is supported over a db link, but if not, then the appropriate date predicates will do the same trick, and then just follow up with:
alter table active_table truncate partition myparname;
I wonder how works the DBA_TAB_MODIFICATIONS.
How long is kept the data for a table? I have tables with timestamp
on Dec/2019
What does it mean when a table is not in
DBA_TAB_MODIFICATIONS? do it mean the table hasn't had (delete,
insert, update) in a period? if yes, for how long?
I have a Schema with around 1000 tables, only around 300 appear in
DBA_TAB_MODIFICATIONS
DBA_TAB_MODIFICATIONS is used by Oracle internally to track how many inserts, updates and deletes have been done to a table or table partition since the stats had been gathered on it with dbms_stats.
What version of Oracle are you using because after Oracle 9 it is automatically inserted
into the DBA_TAB_MODIFICATIONS table, before oracle 9 you have to register a table as MONITORED.
Delete on table in oracle standard edition(no partition) gets slow with time.
Important Info: I am working on oracle standard edition so partitioning option available.
Detail:
I have one table with no constraint on it (no PK or anyother key or trigger or index or anything).
More than a million record gets inserted in this table in every 15 min using sql loader.
we need to process this 15 min record in every 15 min and at end of process delete any record older than 30 minute so that at any point of time there is more than 30-40 minute of data in the table.
Problem:
As time passes due to so frequent insertion and deletion response from the table gets slow.
Data extraction and delete from table takes more time with every passing run.
After a while even a simple select query takes too long.
We cant truncate table as data loader runs continously and we may loose data if truncate and we dont have create table access to drop and create table.
we have to process data in every 15 minute and made it available to downstream for further processing. it just keep getting slow.
Kindly help me with the aforementioned situation.
I am using Oracle9i (9.2). I have a situation where I have to populate a table daily. Daily at mid night this table will be truncated and new data will be put in. The new data population takes about 10-20 mins. The issue is that this table can't be down(locked). While the new data is being inserted, the previous days data needs to be available for a select procedure.
Edit - I am looking into the transaction levels. I just need some expert opinion.
Is this possible in Oracle?
How about using two tables. Have a "current" table that has the previous days data. Then have a new table which you can load. Then when you are ready, you can "swap" the two tables, using a series of rename operations.
I wanna know how hive partitioning works I know the concept but I am trying to understand how its working and store the in exact partition.
Let say I have a table and I have created partition on year its dynamic, ingested data from 2013 so how hive create partition and store the exact data in exact partition.
If the table is not partitioned, all the data is stored in one directory without order. If the table is partitioned(eg. by year) data are stored separately in different directories. Each directory is corresponding to one year.
For a non-partitioned table, when you want to fetch the data of year=2010, hive have to scan the whole table to find out the 2010-records. If the table is partitioned, hive just go to the year=2010 directory. More faster and IO efficient
Hive organizes tables into partitions. It is a way of dividing a table into related parts based on the values of partitioned columns such as date.
Partitions - apart from being storage units - also allow the user to efficiently identify the rows that satisfy a certain criteria.
Using partition, it is easy to query a portion of the data.
Tables or partitions are sub-divided into buckets, to provide extra structure to the data that may be used for more efficient querying. Bucketing works based on the value of hash function of some column of a table.
Suppose you need to retrieve the details of all employees who joined in 2012. A query searches the whole table for the required information. However, if you partition the employee data with the year and store it in a separate file, it reduces the query processing time.