As I known about the relational database, records are stored with the same size. However, array datatype in PostgreSQL is flexible in size. So how PostgreSQL actually store Array datatype? Do it store the pointer of the array to the record and store the value somewhere else?
In PostgreSQL (and other databases I am aware of) rows do not have a fixed size.
Arrays are stored like all other values of a type with variable size: if the row threatens to exceed 2000 bytes, the TOAST machinery will first compress such values, and if that is not enough, store them out of line in a TOAST table.
See the documentation for details.
Related
I am wondering about the memory allocation in database whether it assign the memory on the base of DataType of the column or it assign according to the value. Being a .net developer i have the concept that memory allocation is assign on the bases of DataType not on the value. Now I have question how memory allocation is handled on DB side.
FOR EXAMPLE
| id1 | id2 | id3 | name
| NULL | NULL | NULL | James Bond
id1,id2,id3 has null values, what will be the memory size of this row. will it assign the memory to the columns having null values?
Edit
Database Server SQLServer2008 r2
Thanks in advance
Physical storage for SQL Server is in a unit called a "page". There are several structures within a page, those structures are called "records". There are several types of records, the type of record you seem to be asking about is called a "data record".
(There are also several other types of records within a page: index records, forwarding records, ghost records, text records, and other internal record structures (allocation bitmaps, file headers, etc.)
To answer your question, without delving into all those details, and neglecting a discussion of "row compression" and "page compression"...
One part of the record is for the "fixed length" columns, where the columns that are defined with fixed length datatypes are stored (integer, float, date, char(n), etc.). As the name implies, a fixed amount of storage is reserved for each column. Another part of the record is the "variable length" portion, where columns with datatypes of variable length are stored, arranged as an array, a two-byte count of the number of variable length columns, and for each column, a two-byte offset to the end of the column value.
Q: what will be the memory size of this row.
A: In your case, the table with four columns, there will be eight bytes for the record header, some fixed number of bytes for the fixed length columns, three bytes for the NULL bitmap, and a variable amount of storage for the variable length columns.
The "memory size for the row" is really determined by the datatypes of the columns, and for variable length columns, the values that are stored.
(And if any indexes exist, there's also space required in index records.)
Q: will it assign the memory to the columns having null values?
If the columns are fixed length, yes. If columns are variable length, yes, at a minimum, the two byte offset to the end of the value, even if the value is zero length.
SQL Server manages memory in "pages"... In terms of estimating memory requirements, the more pertinent question is "how many rows fit in a page", and "how many pages are required to store my rows?"
A page that contains one data record requires 4KB of memory. A page that contains a dozen data records requires 4KB of memory.
I have found the answer on MSDN
Use Sparse Columns
The SQL Server Database Engine uses the SPARSE keyword in a column definition to optimize the storage of values in that column. Therefore, when the column value is NULL for any row in the table, the values require no storage.
http://msdn.microsoft.com/en-us/library/cc280604.aspx
I am trying to write a small blog engine. I would love to find a sample SQL Server schema to give me some ideas but have yet to find one.
I would like to have a blog table that allows me to store more than 8000 bytes of data. Can anyone tell me if a good way to do this would with two fields like this:
CREATE TABLE [Blog](
[BlogId] [int] IDENTITY(1,1) NOT NULL,
[BlogText1] [nvarchar](8000) NOT NULL,
[BlogText2] [nvarchar](8000),
..
What I was thinking was to store the text in two fields and have my application append the contents of the two fields when it was displaying the data and when storing data have the first xxx characters stored in BlogText1 and then any remainder stored in BlogText2.
Is this a reasonable thing to do or should I just use a nvarchar(max)?
If I use nvarchar(8000) how many characters can I fit into that?
What I am concerned about is the time it will take to retrieve a row. Am I correct in assuming that if I use nvarchar(max) it will take much longer to retrieve the row.
The short version - use NVARCHAR(MAX) until you identify that there is a definite performance problems to solve - attempting to manually split up large blog entries so that they are saved "inline" is almost certainly going to result in worse performance than leaving it up to SQL Server.
The long version - SQL Server stores data up in 8060 byte size chunks called pages. Normally the length of an individual column cannot exceed this size, however certain large-value types (e.g. TEXT) can be handled specially and their value replace with a 24-byte pointer to the actual data which is stored elsewhere (in the ROW_OVERFLOW_DATA allocation unit)
The NVARCHAR(MAX) data types actually provide a hybrid approach - in the case where the data is small enough the value is stored in the Data pages as it would be normally, however when the data is too large it is seamlessly converted into a large-value type for you. This generally means you get the best of both worlds.
Have been reading up on Hadoop and HBase lately, and came across this term-
HBase is an open-source, distributed, sparse, column-oriented store...
What do they mean by sparse? Does it have something to do with a sparse matrix? I am guessing it is a property of the type of data it can store efficiently, and hence, would like to know more about it.
In a regular database, rows are sparse but columns are not. When a row is created, storage is allocated for every column, irrespective of whether a value exists for that field (a field being storage allocated for the intersection of a row and and a column).
This allows fixed length rows greatly improving read and write times. Variable length data types are handled with an analogue of pointers.
Sparse columns will incur a performance penalty and are unlikely to save you much disk space because the space required to indicate NULL is smaller than the 64-bit pointer required for the linked-list style of chained pointer architecture typically used to implement very large non-contiguous storage.
Storage is cheap. Performance isn't.
Sparse in respect to HBase is indeed used in the same context as a sparse matrix. It basically means that fields that are null are free to store (in terms of space).
I found a couple of blog posts that touch on this subject in a bit more detail:
http://blog.rapleaf.com/dev/2008/03/11/matching-impedance-when-to-use-hbase/
http://jimbojw.com/wiki/index.php?title=Understanding_Hbase_and_BigTable
At the storage level, all data is stored as a key-value pair. Each storage file contains an index so that it knows where each key-value starts and how long it is.
As a consequence of this, if you have very long keys (e.g. a full URL), and a lot of columns associated with that key, you could be wasting some space. This is ameliorated somewhat by turning compression on.
See:
http://www.larsgeorge.com/2009/10/hbase-architecture-101-storage.html
for more information on HBase storage
There are two way of data storing in the tables it will be either Sparse data and Dense data.
example for sparse data.
Suppose we have to perform a operation on a table containing sales data for transaction by employee between the month jan2015 to nov 2015 then after triggering the query we will get data which satisfies above timestamp condition
if employee didnt made any transaction then the whole row will return blank
eg.
EMPNo Name Product Date Quantity
1234 Mike Hbase 2014/12/01 1
5678
3454 Jole Flume 2015/09/12 3
the row with empno5678 have no data and rest of the rows contains the data if we consider whole table with blanks row and populated row then we can termed it as sparse data.
If we take only populated data then it is termed as dense data.
The best article I have seen, which explains many databases terms as well.
> http://jimbojw.com/#understanding%20hbase
I have an issue where I have one column in a database that might be anything from 10 to 10,000 bytes in size. Do you know if PostgreSQL supports sparse data (i.e. will it always set aside the 10,000 bytes fore every entry in the column ... or only the space that is required for each entry)?
Postgres will store long varlena types in an extended storage called TOAST.
In the case of strings, it keep things inline up to 126 bytes (potentially means less 126 characters for multibyte stuff), and then sends it to the external storage.
You can see where the data is stored using psql:
\dt+ yourtable
As an aside, note that from Postgres' standpoint, there's absolutely no difference (with respect to storage) between declaring a column's type as varchar or varchar(large_number) -- it'll be stored in the exact same way. There is, however, a very slight performance penalty in using varchar(large_number) because of the string length check.
use varchar or text types - these use only the space actually required to store the data (plus a small overhead of 2 bytes for each value to store the length)
My fellow programmer has a strange requirement from his team leader; he insisted on creating varchar columns with a length of 16*2n.
What is the point of such restriction?
I can suppose that short strings (less than 128 chars for example) a stored directly in the record of the table and from this point of view the restriction will help to align fields in the record, larger strings are stored in the database "heap" and only the reference to this string is saved in the table record.
Is it so?
Is this requirement has a reasonable background?
BTW, the DBMS is SQL Server 2008.
Completely pointless restriction as far as I can see. Assuming standard FixedVar format (as opposed to the formats used with row/page compression or sparse columns) and assuming you are talking about varchar(1-8000) columns
All varchar data is stored at the end of the row in a variable length section (or in offrow pages if it can't fit in row). The amount of space it consumes in that section (and whether or not it ends up off row) is entirely dependant upon the length of the actual data not the column declaration.
SQL Server will use the length declared in the column declaration when allocating memory (e.g. for sort operations). The assumption it makes in that instance is that varchar columns will be filled to 50% of their declared size on average so this might be a better thing to look at when choosing a size.
I have heard of this practice before, but after researching this question a bit I don't think there is a practical reason for having varchar values in multiples of 16. I think this requirement probably comes from trying to optimize the space used on each page. In SQL Server, pages are set at 8 KB per page. Rows are stored in pages, so perhaps the thinking is that you could conserve space on the pages if the size of each row divided evenly into 8 KB (a more detailed description of how SQL Server stores data can be found here). However, since the amount of space used by a varchar field is determined by its actual content, I don't see how using lengths in multiples of 16 or any other scheme could help you optimize the amount of space used by each row on the page. The length of the varchar fields should just be set to whatever the business requirements dictate.
Additionally, this question covers similar ground and the conclusion also seems to be the same:
Database column sizes for character based data
You should always store the data in the data size that matches the data being stored. It is part of how the database can maintain integrity. For instance suppose you are storing email addresses. If your data size is the size of the maximum allowable emailaddress, then you will not be able to store bad data that is larger than that. That is a good thing. Some people want to make everything nvarchar(max) or varchar(max). However, this causes only indexing problems.
Personally I would have gone back to the person who make this requirement and asked for a reason. Then I would have presented my reasons as to why it might not be a good idea. I woul never just blindly implement something like this. In pushing back on a requirement like this, I would first do some research into how SQL Server organizes data on the disk, so I could show the impact of the requirement is likely to have on performance. I might even be surprised to find out the requirement made sense, but I doubt it at this point.