i have to insert a very long string ~ 65KB into two column in the table each. But in netezza, table size is limited to ~ 65KB. Is there any way like CLOB or dynamic datatype or anything that can store such long string in NZ table.
Thanks.
Short answer: No
You'll need to do a horizontal partition and put each large string column in its own table with a common integer primary key.
Related
I have a table in snowflake with around 1000 columns, i have an id column which is of integer type
when i run query like
select * from table where id=12
it is scanning all the micro-paritions .I am expecting that snowflake will maintain metadata of min/max of id column and based on that it should scan only one partition rather than all the partition.
In this doc https://docs.snowflake.com/en/user-guide/tables-clustering-micropartitions.html its mentioned that they maintain min/max , disticnt value of columns in each micro-partition.
How can i take advantage of partititon pruning in this scenario?Currently even for unique id snowflake is scanning all the partitions.
It's a little more complicated than that unfortunately. Snowflake would only scan a single partition if your table was perfectly clustered by your id column, which it probably isn't, nor should it be. Snowflake is a data warehouse and isn't ideal for single-row lookups.
You could always cluster your table by your id column but you usually don't want to do this in a data warehouse. I would recommend reading this document to understand how table clustering works.
I have a big table on my database, but it has a lot of empty fields on every column, and I´d like to know how much does every column use.
Is there any way to know how much disk space is each tables columns using?
Try using pg_column_size(), it will return the column size in bytes:
SELECT sum(pg_column_size(column)) FROM yourtable
As the documentation mentions, NULL values are indicated in the null bitmap of every tuple, which is always present if the table has nullable columns.
So a NULL value consumes no extra space on disk.
If you design tables with very many columns, rethink your design.
I have a some tables(Table A and Table B) with a BIGINT with IDENTITY specification as primary key.
In those tables I have 2 VARBINARY(MAX) columns. Updates and deletes are very rare.
They have with almost the same row count, Table B a bit less but have significant more data in the VARBINARY(MAX) columns.
I was surprised to see that the storage used by PK in Table B was much higher than the storage used by PK in Table A.
Doing some reading, correct me if I am wrong, on the subject clarified that is has some thing to do with the max row size around 8k. So the there is some paging going on with a byte reference which is then included in the index. Hence the larger storage used by PK in Table B. It is around 30 percent of the total size of the DB.
I was of the assumption that only the BIGINT was part of the index.
My question is whether there is a workaround for that? Any designs, techniques or hacks that can prevent this?
Regards
Vilma
A PK is a CLUSTERED index: the data is stored with the key. You can have only one clustered index per table, because the data can only be stored in one place. So any clustered index (such as a PK) will take up more space than a non-clustered index.
If there is more varbinary table in B, then I would expect the PK to take up more space.
However, since this varbinary is (MAX) then the initial thought is that only the data pointer should be stored with the key. However, if the row is small enough (i.e. < 8000 bytes) I imagine that SQL Server optimises the store/retrieve by keeping the data with the key, thus increasing the size of the index. I do not know that this happens, but was unable to find anything to say it doesn't; as an optimisation is seems reasonable.
Take that for what it's worth!
I was given a ragtag assortment of data to analyze and am running into a predicament. I've got a ~2 million row table with a non-unique identifier of datatype varchar(50). This identifier is unique to a personID. Until I figure out exactly how I need to normalize this junk I've got another question that might help me right now: If I change the datatype to a varchar(25) for instance, will that help queries run faster when they're joined on a non-PK field? All of the characters in the string are integers, but trying to convert them to an int would cause overflow. Or could I possibly somehow index the column for the time being to get some of the queries to run faster?
EDIT: The personID will be a foreign key to another table with demographic information about a person.
Technically, the length of a varchar specifies it's maximum length.
The actual length is variable (thus the name) so a lower maximum value won't change the evaluation because it will be made on the actual string.
For more information :
Check this MSDN article and this
Stack overflow Post
Varchar(50) to varchar(25) would certainly reduce the size of record in that table, thereby reducing the number of database pages that contain the table, improving the perfomance of queries (may be to a marginal extent), but such an ALTER TABLE statement might take a long time.
Alternatively, if you define index on the join columns, and if your retrieval list is small, you can include those columns also in the index definition (Covering index), that too would bring down the query execution times significantly.
I have a SQL Server 2008 database with a table that has 575 columns in it. I have a CSV file that matches the table.
When I use SqlBulkCopy (.NET 4), only the first 256 columns get populated. The rest get nulls inserted into them. Has anyone else experienced this issue?
Thanks,
ts3
I'm going to guess that your primary key column is autoincrementing from zero and it is of type tinyint. If so then you should change your primary key on that column to be an integer or something that can hold more values.