I have a table that is partitioned by hash on a column.
CREATE TABLE TEST(
ACCOUNT_NUMBER VARCHAR(20)
)
PARTITION BY HASH (ACCOUNT_NUMBER)
PARTITIONS 16
Now, I want to update the account_number column itself in the table because of certain requirements.
As this column is partitioned, I'm not able to issue an update command on the table like
Update test set account_number = new_value
as it results to the below error:
Error is: ORA-14402: UPDATING PARTITION WOULD CAUSE PARTITION CHANGE.
Row movement is set to disable for the table.
The one way I know is to enable row movement but I also want to explore other options.
Could you please advise me on how to solve this?
Related
I am trying to insert extracted data from a sql table into a postgres table where the rows may or may not exist. If they do exist, I would like to set a specific column to its default (0)
The table is as
site_notes (
job_id text primary key,
attachment_id text,
complete int default 0);
My query is
INSERT INTO site_notes (
job_id,
attachment_id
)
VALUES
{jobs_sql}
ON CONFLICT (job_id) DO UPDATE
SET complete = DEFAULT;
However I am getting an error: psycopg2.errors.CardinalityViolation: ON CONFLICT DO UPDATE command cannot affect row a second time
HINT: Ensure that no rows proposed for insertion within the same command have duplicate constrained values.
Would anyone be able to advise on how to set the complete column to the default on event of a conflict ?
Many Thanks
An INSERT ... ON CONFLICT DO UPDATE statement (and indeed an UPDATE statement too) is not allowed to modify the same row more than once. It is not clear what {jobs_sql} in your question is, but it must contain several rows, and at least two of those have the same job_id.
Make sure that the same job_id does not occur more than once in the rows you want to INSERT.
This question is for a database using PostgreSQL 12.3; we are using declarative partitioning and ON CONFLICT against the partitioned table is possible.
We had a single table representing application event data from client activity. Therefore, each row has fields client_id int4 and a dttm timestamp field. There is also an event_id text field and a project_id int4 field which together formed the basis of a composite primary key. (While rare, it was possible for two event records to have the same event_id but different project_id values for the same client_id.)
The table became non-performant, and we saw that queries most often targeted a single client in a specific timeframe. So we shifted the data into a partitioned table: first by LIST (client_id) and then each partition is further partitioned by RANGE(dttm).
We are running into problems shifting our upsert strategy to work with this new table. We used to perform a query of INSERT INTO table SELECT * FROM staging_table ON CONFLICT (event_id, project_id) DO UPDATE ...
But since the columns that determine uniqueness (event_id and project_id) are not part of the partitioning strategy (dttm and client_id), I can't do the same thing with the partitioned table. I thought I could get around this by building UNIQUE indexes on each partition on (project_id, event_id) but the ON CONFLICT is still not firing because there is no such unique index on the parent table (there can't be, since it doesn't contain all partitioning columns). So now a single upsert query appears impossible.
I've found two solutions so far but both require additional changes to the upsert script that seem like they'd be less performant:
I can still do an INSERT INTO table_partition_subpartition ... ON CONFLICT (event_id, project_id) DO UPDATE ... but that requires explicitly determining the name of the partition for each row instead of just INSERT INTO table ... once for the entire dataset.
I could implement the "old way" UPSERT procedure: https://www.postgresql.org/docs/9.4/plpgsql-control-structures.html#PLPGSQL-UPSERT-EXAMPLE but this again requires looping through all rows.
Is there anything else I could do to retain the cleanliness of a single, one-and-done INSERT INTO table SELECT * FROM staging_table ON CONFLICT () DO UPDATE ... while still keeping the partitioning strategy as-is?
Edit: if it matters, concurrency is not an issue here; there's just one machine executing the UPSERT into the main table from the staging table on a schedule.
I would like to create an auto-incrementing id column that is not a primary key in a PostgreSQL table. The table is currently just over 200M rows and contains 14 columns.
SELECT pg_size_pretty(pg_total_relation_size('mytable'));
The above query reveals that mytable takes up 57 GB on disk. I currently have 30 GB free space remaining on disk after checking with df -h (on Ubuntu 20.04)
What I don't understand is why, after trying to create a SERIAL column, I completely run out of disk space - the query ends up never finishing. I run the following command:
ALTER TABLE mytable ADD COLUMN id SERIAL;
and then see how gradually, my disk space runs out until there is nothing left and the query fails. I am no database expert but it does not make sense. Why would a simple serialized column take up more than half of the space of the table itself, especially when it is not a primary key and therefore has no index? Is there a known workaround to creating such an auto-incrementing id column?
As a proof of concept:
create table id_test(pk_fld integer primary key generated always as identity);
--FYI, in Postgres 14+ the overriding system value won't be needed.
--That is a hack around a bug in 13-
insert into id_test overriding system value values (default), (default);
select * from id_test;
pk_fld
--------
1
2
alter table id_test add column id_fld integer ;
update id_test set id_fld = 0;
alter table id_test alter COLUMN id_fld set not null;
alter table id_test alter COLUMN id_fld add generated always as identity;
update id_test set id_fld = default;
select * from id_test;
pk_fld | id_fld
--------+--------
1 | 1
2 | 2
Basically this breaks the process down into steps. Obviously this is just a toy table and not representative of your setup. I would try it on test table that is a subset of you actual table to see what happens to disk space consumption. It would not hurt to use VACUUM after the updates to return rows to the database.
Adding a serial column is adding an integer column with a non-constant DEFAULT value. This will cause PostgreSQL to rewrite the table, because the new column value has to be added to all existing rows. So PostgreSQL writes a new copy of the table and discards the old one after it is done. This will require more than double the disk space of the original table temporarily, which explains why you run out of disk space.
You can split the operation into several steps:
ALTER TABLE mytable ADD id bigint;
CREATE SEQUENCE mytable_id_seq OWNED BY mytable.id;
ALTER TABLE mytable ALTER id SET DEFAULT nextval('mytable_id_seq');
This will not rewrite the table, and it will leave the existing rows untouched. The value of id for these columns will be NULL.
You probably want to update the existing rows to be NOT NULL, but be careful: if you update them all at once, you will run out of disk space as well, because in PostgreSQL an UPDATE writes a complete new version of the row to the table. You'd have to update the rows in batches and run VACUUM between these updates.
All in all, this is rather annoying and complicated. So do yourself a favor and increase the disk space. That is the simple and best solution.
I want to partition an external table in hive based on range of numbers. Say numbers with 1 to 100 go to one partition. Is it possible to do this in hive?
I am assuming here that you have a table with some records from which you want to load data to an external table which is partitioned by some field say RANGEOFNUMS.
Now, suppose we have a table called testtable with columns name and value. The contents are like
India,1
India,2
India,3
India,3
India,4
India,10
India,11
India,12
India,13
India,14
Now, suppose we have a external table called testext with some columns along with a partition column say, RANGEOFNUMS.
Now you can do one thing,
insert into table testext partition(rangeofnums="your value")
select * from testtable where value>=1 and value<=5;
This way all records from the testtable having value 1 to 5 will come into one partition of the external table.
The scenario is my assumption only. Please comment if this is not the scenario you have.
Achyut
I have one master table. its primary key is used as foreign key in other tables. I can not modify the definition of the other tables as it does not have any "on update cascade" and i want to change the primary key's value so the other tables i should update...
currently i have written the plpgsql,
but as I have large amount of data to process, somehow it is slowing down the performance.
Can someone help me, how to update multiple table in single query, or updating multiple rows of-course with different values?
Here's one option to update multiple rows in one statement:
update mytable set
mycolumn = (case myid when 1 then 'a' when 2 then 'b' ... end)
where myid in (1, 2, ...);