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What is the fastest way to add indices and an ID primary key column to a large table?


What is the fastest way to add indices and an ID primary key column to a large table?

By : John Blatchford
Date : November 19 2020, 03:01 PM
it should still fix some issue First, your command doesn't create four indices. It creates two indices in which the first is a composite index (which may not be exactly what you want because column order matters whether or not the planner will choose to use the index).
Second, are you executing the CREATE commands serially? Could you run all 300 create commands in parallel?
code :
tableList = ['table1', 'table2', 'table3', ...]
createSql = 'CREATE INDEX...[0]...'
[executeInThread(table) for table in tableList]


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Postgresql fastest way of getting the set of unique values in one column or a large table

Postgresql fastest way of getting the set of unique values in one column or a large table


By : Marlon Alucard
Date : March 29 2020, 07:55 AM
I hope this helps you . For option 1, what you want to do is a "loose index scan", or a "skip scan".
It would be nice if PostgreSQL would automatically do those when they are beneficially, but as of now it does not do that. But you can trick it into it. I've never tried this on a partitioned table, but I think it would be simple matter of adding the suitable WHERE clause to each branch of the union all.
Python: Fastest way of parsing first column of large table in array

Python: Fastest way of parsing first column of large table in array


By : user3952217
Date : March 29 2020, 07:55 AM
it should still fix some issue So I have got two very big tables that I would like to compare (9 columns and approx 30 million rows). , A few suggestions:
code :
sam1_identifiers = set()
for line in reader1:
    sam1_identifiers.add(line[0])
sam2_identifiers = set()
for line in reader2:
    sam2_identifiers.add(line[0])

print sam1 - sam2
sam2_identifiers = set()
for line in reader2:
    sam1_identifiers.discard(line[0])

print sam1_identifiers
Fastest way to trim one column's data in large MySQL table

Fastest way to trim one column's data in large MySQL table


By : smcfarlane
Date : March 29 2020, 07:55 AM
it helps some times I would walk through that table in "chunks", doing perhaps 1000 rows at a time. Here is some pseudo code. (The details depend on the language you wish to write this in.)
code :
$a = '';  -- assuming this is less than any value
loop...
    $z = SELECT v FROM main
        WHERE v > $a  ORDER BY v  LIMIT 1000,1;  -- efficient locate stopper
    BEGIN;
    -- Update each table
    UPDATE main SET v = TRIM(v)
        WHERE v > $a AND v <= $z;
    UPDATE table2 SET v = TRIM(v)
        WHERE v > $a AND v <= $z;
    UPDATE table3 SET v = TRIM(v)
        WHERE v > $a AND v <= $z;
    COMMIT;   -- this keeps anyone from stumbling over FKs in transition
    if finished, exit loop
    $a = $z
end loop
What is the fastest way to query in batches a large xml stored in xmltype column in oracle database table?

What is the fastest way to query in batches a large xml stored in xmltype column in oracle database table?


By : Alaa AlHasan
Date : March 29 2020, 07:55 AM
Does that help I have figured out a couple of ways of doing this with one sql query.
Approach 1:
Should I apply both PRIMARY and UNIQUE indices on an id column of a MySQL InnoDB table?

Should I apply both PRIMARY and UNIQUE indices on an id column of a MySQL InnoDB table?


By : HoorayItsMike
Date : March 29 2020, 07:55 AM
it should still fix some issue Having an InnoDB table with a simple single-column synthetic id primary key, should I only use PRIMARY index on the id column, or UNIQUE index too? Why? , Pk is enough, as it is also a unique key
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