I have a non-partitioned table record which is append-only and I intended to partition it by range of created timestamp column using postgres native partition. (one partition per month)
I can tolerate a bit of downtime, so my plan is:
Create new table record_partitioned with partitions; copy all past month’s data into new partitioned table
Stop write into the table, copy current month’s data into new partitioned table (a bit of downtime)
Rename old table as record_archived, and rename new table as record
Resume write into table
Does this make sense?
That should work, but you can also consider the following:
create a new partitioned table
add a partition for the current month
attach the existing large table as a partition for all past data
once all data in the existing table have expired, drop it
Related
I have workloads that have heavy schema changes and other ETL operations that are locking.
Before doing schema changes on my primary table, I would like to first copy the existing contents from the primary table on to a temporary table, then perform the schema change, then sync all new changes and once the "time is right" (cutoff?), do the cut over and have the temporary table become the primary table.
I know that I can use Triggers in postgres to sync data between two tables, and also use COPY to copy data from one table to another.
But I am not sure how can I can copy existing data first, then issue trigger to ensure no data is lost. Then also do the cut off so that the new table is primary.
What I am thinking is -
I issue a COPY table from primary table (TableA) to temp table TableB.
I then perform the schema change in TableB
I then setup Trigger from TableA to TableB for INSERT/UPDATE/DELETE
... Now I am not sure how can I cut off so TableB becomes TableA. I can use RENAME perhaps?
It feels like I can run into some lost changes between Step 1 and Step 2?
Basically I am trying to ensure no data between the three high level operations. Is there a better way to do this?
So basically we have a very large table in Postgres 11 DB which has hundreds of millions of data since the table was added. Now we are trying to convert it into a range based partition table based on created_at column (timestamp - not nullable).
As suggested in the Postgres Partitioning Documentation, I tried adding a check constraint on the same table before actually running the attach partition. So after that if I run attach partition, ideally it should have taken very less time as it should skip the validation due to presence of respective constraint on the table, but I see it is still taking lot more time. My partition range and the constraint looks something like this:
alter table xyz_2020 add constraint temp_check check (created_at >= '2020-01-01 00:00:00' and created_at < '2021-01-01 00:00:00');
ALTER TABLE xyz ATTACH PARTITION xyz_2020 FOR VALUES FROM ('2020-01-01 00:00:00') TO ('2021-01-01 00:00:00');
Here xyz_2020 is my existing big table which got renamed from xyz. And xyz is the new master table created like the old table. So I want to understand what could be the possible reasons that attach partition might still be taking lot more time.
Edit: We are creating a new partitioned table and trying to attach the old table as one of its partition.
We have existing table of size more than 130 TB we have to delete records in DB2 . Using delete statement would will hang the system. So one way is we can partition the table month and year wise and then drop the partition one by one by using truncate or drop. Looking for a script which can create the partition and subsequently dropping.
You can't partition the data within an existing table. You would need to move the data to a new ranged partitioned table.
If using Db2 LUW, and depending on your specific requirments, consider using ADMIN_MOVE_TABLE to move your data to a new table while keeping your table "on-line"
ADMIN_MOVE_TABLE has the ability to add Range Partitioning and/or Multi-Dimentional Clustering on the new table during the move.
https://www.ibm.com/support/knowledgecenter/en/SSEPGG_11.5.0/com.ibm.db2.luw.sql.rtn.doc/doc/r0055069.html
Still, a 130 TB table is very large, and you would be well advised to be carful in planning and testing such a movement.
I'm new to table partitions in Postgres and have one doubt.
Let us assume I have a table:
product_visitors
I can create multiple partitions like:
product_visitors_year_2017
product_visitors_year_2018
etc.
I can create a trigger which can redirect insertion on product_visitors to appropriate table.
My question is, what if I want to aggregate on full data of product_visitors? For example, products and their visit count
As I understand, at the moment, data resides in year wise tables instead of main table
In Postgres 10 inserts will automatically be routed to the correct partition.
If you select from the "base table" product_visitors without any condition limiting the rows to one (or more) specific partitions, Postgres will automatically read the data from all partitions.
So
select count(*)
from product_visitors;
will count the rows in all partitions.
I know how partitioning in DB2 works but I am unaware about where this partition values exactly get stored. After writing a create partition query, for example:
CREATE TABLE orders(id INT, shipdate DATE, …)
PARTITION BY RANGE(shipdate)
(
STARTING '1/1/2006' ENDING '12/31/2006'
EVERY 3 MONTHS
)
after running the above query we know that partitions are created on order for every 3 month but when we run a select query the query engine refers this partitions. I am curious to know where this actually get stored, whether in the same table or DB2 has a different table where partition value for every table get stored.
Thanks,
table partitions in DB2 are stored in tablespaces.
For regular tables (if table partitioning is not used) table data is stored in a single tablespace (not considering LOBs).
For partitioned tables multiple tablespaces can used for its partitions.
This is achieved by the "" clause of the CREATE TABLE statement.
CREATE TABLE parttab
...
in TBSP1, TBSP2, TBSP3
In this example the first partition will be stored in TBSP1, the second in TBSP2, The third in TBSP3, the fourth in TBSP1 and so on.
Table partitions are named in DB2 - by default PART1 ..PARTn - and all these details can be looked up in the system catalog view SYSCAT.DATAPARTITIONS including the specified partition ranges.
See also http://www-01.ibm.com/support/knowledgecenter/SSEPGG_10.5.0/com.ibm.db2.luw.sql.ref.doc/doc/r0021353.html?cp=SSEPGG_10.5.0%2F2-12-8-27&lang=en
The column used as partitioning key can be looked up in syscat.datapartitionexpression.
There is also a long syntax for creating partitioned tables where partition names can be explizitly specified as well as the tablespace where the partitions will get stored.
For applications partitioned tables look like a single normal table.
Partitions can be detached from a partitioned table. In this case a partition is "disconnected" from the partitioned table and converted to a table without moving the data (or vice versa).
best regards
Michael
After a bit of research I finally figure it out and want to share this information with others, I hope it may come useful to others.
How to see this key values ? => For LUW (Linux/Unix/Windows) you can see the keys in the Table Object Editor or the Object Viewer Script tab. For z/OS there is an Object Viewer tab called "Limit Keys". I've opened issue TDB-885 to create an Object Viewer tab for LUW tables.
A simple query to check this values:
SELECT * FROM SYSCAT.DATAPARTITIONS
WHERE TABSCHEMA = ? AND TABNAME = ?
ORDER BY SEQNO
reference: http://www-01.ibm.com/support/knowledgecenter/SSEPGG_9.5.0/com.ibm.db2.luw.sql.ref.doc/doc/r0021353.html?lang=en
DB2 will create separate Physical Locations for each partition. So each partition will have its own Table-space. When you SELECT on this partitioned Table your SQL may directly go to a single partition or it may span across many depending on how your SQL is. Also, this may allow your SQL to run in parallel i.e. many TS can be accessed concurrently to speed up the SELECT.