When we create a columnstore index on a huge table,does it use a separate physical storage on disk to store the coulmn store index or it changes the storage structure of the base table from row-stoarge to column store.
Here my question is, when we create normal index on any table, it store sthe indexed column data into a b-tree using separate storage without affecting base table,the same way columnstore index does?
Only nonclusterd columnstore indexes are supported in SQL Server 2012 so the table itself will not be reorganized.
http://msdn.microsoft.com/en-us/library/gg492153.aspx
NONCLUSTERED
Creates a columnstore index that specifies the logical ordering of a table. Clustered columnstore indexes are not supported.
Indexes (with the exception of the clustered index which is the table its self) are stored in separate locations, they can have their own packing (space allowed for futher inserts without the tree becoming too unbalanced) and even be stored on separate drives: CREATE INDEX ....ON PRIMARY, SECONDARY etc. You have to create the SECONDARY and further files before creating the index and allocating to the File. Indexes are allocated to the logical file name. You can reduce costs and increase speed by having these as single rather than RAID drives, as in case of failure the index can be rebuilt without data loss. http://msdn.microsoft.com/en-us/library/ms188783.aspx and http://msdn.microsoft.com/en-us/library/gg492088.aspx
Related
We are working with U-SQL tables and have questions related to Clustered Index. In U-SQL table, parallelism is managed by how data is partitioned and distributed. Does Clustered Index impact parallelism as well in U-SQL table? Secondly how it manages data skew in a distribution bucket?
Clustered index is not impacting parallelism per se, but it may impact if you read the data using an index seek or index scan depending on the query predicate. So it impacts the performance of accessing the data inside a vertex.
Data skew is not managed. If you have skew you will have to either find a better distribution key, use a skewfactor hint or use ROUND ROBIN distribution.
Am little confused with clustered index and non clustered index.
is any differences in MySQL and DB2 regarding clustered Indexing ?
In DB2, any single index on a table can be designated as the table's clustering index. The index is a normal b-tree index, no different (physically) than any other index other than the fact that it's been identified as the clustering index. The index has a series of index keys, and each index key has a list of RIDs (row IDs) that point to the physical location of the data for each row that matches the index key.
If you reorganize the table (using the REORG TABLE utility) DB2 will physically arrange the table's data (which is separate from the index's data) in the same physical order as the clustering index. DB2 will attempt to maintain the physical clustering order as new rows are inserted into the table (and you can help it by choosing an appropriate value for table's PCTFREE attribute), but over time the cluster ratio may decrease and you may need to reorganize the table again.
Compare this with MySQL, where with InnoDB, the table's data is stored in the primary key index's structure. So, unlike DB2 where the index has the key columns and then a list of RIDs, the primary key index stores the entire row – there is no separate storage object holding the table's data. This is why it's called a clustered index rather than a clustering index. This massively increases the size of the physical index, making it significantly harder to ensure that it will remain cached in memory.
Secondary indexes in InnoDB store the index key and the primary key columns for the rows (rather than a RID) – this could be inefficient if the primary key is made up of many columns.
<soapbox>
Using the primary key (or any unique key) for "clustering" is ridiculous. The entire point of clustering it to maintain locality of related data. InnoDB is not alone here - Microsoft SQL Server does this as well.
Take, for example, a transaction table. The primary key for this table may be transaction_id. With InnoDB, this is the clustered index. However, the likelihood that one transaction ID is related to the next transaction ID is pretty low.
account_id would make a much better clustering key precisely because it is not unique. If I'm looking for all transactions for a particular account_id, having all of those rows on a single physical page makes a lot of sense and greatly will reduce the amount of I/O necessary to find all of those rows.
If the table's data is stored as part of the primary key's structure (i.e. on transaction_id), then you'll likely be reading pages from all over the index just to find all of the transactions for a single account.
You may argue that storing all of the data as part of the primary key is a performance benefit (i.e., 1 I/O to get any particular row), but this also means that caching the index has just become a lot harder because it will be much bigger. "In memory" may be de rigueur, but if you need as much RAM as the size of your database to maintain performance that's useful only up to a point.
</soapbox>
We have a range partitioned table and about 10 bitmap local indexes for that table. We perform some ddl/dml operations on that table in our daily load, which is truncate a specific partition and load data. when we do this, the local bitmap indexes are not becoming unusable. They are in usable status. However, my question is, even though the indexes are not getting unusable, do we always need to incorporate index rebuilding as part of the best practice for range partitioned tables, or use the index rebuilding only when it is required? because index rebuilding takes time, imagine we have 10 local indexes on that table which has large volume, then it becomes a costly affair for etl.
Please provide me your suggestions or thoughts in this situation?
No a rebuild of local indexes is not required, that is one of the main purpose of an local index.
Local partitioned indexes actually create 'sub index' for each partition, so such 'sub index' can be managed independently from other partitions. And when you truncate partition all its local indexes are truncated either.
Oracle doc:
"You cannot truncate an index partition. However, if local indexes are
defined for the table, the ALTER TABLE ... TRUNCATE PARTITION
statement truncates the matching partition in each local index."
So when you load data to that partition it recreate local indexes. But statistic on that index could be wrong and optimizer can consider don't use index. So consider gathering statistics from such indexes if you don't do it.
I was reding this post by Pinal Dave and found this line:
Unindexed tables are good for fast storing of data. Many times, it is
better to drop all the indexes from table and then do bulk of INSERTs
and restore those indexes after that.
Is that really an effective technique in the case of clustered indexes? I mean, won't it be an overhead then to recreate all those indexes again? And I have also read that records are physically stored in the same order as that of logical records when clustered indexes are used. Then how will this affect the physical storage of records when we drop the index and restore them later?
He's partially correct.
Tables without clustered indexes (known as "heaps") are useful for staging tables for bulk loads. These staging tables are not your final tables. For example, the data you load may be data you already have so you only need to find new, changed and deleted records for your final table.
And yes, it is an overhead to recreate the clustered index. When dropped, data will be allocated wherever. When rebuilt, it will rearrange data on disk.
Just for knowledge in interview question, and my knowledge.
SQL - Difference between Cluster and Non-cluster index?
A link describing the two.
http://www.mssqlcity.com/FAQ/General/clustered_vs_nonclustered_indexes.htm
http://www.sql-server-performance.com/articles/per/index_data_structures_p1.aspx
The difference is in the physical order of the records in the table relative to the index. A clustered index is physically ordered that way in the table.
Cluster Index
1 A cluster index is a form of tables which consist of column and rows.
2 Cluster index exists on the physical level
3 It sorts the data at physical level
4 It works for the complete table
5 There is a whole table in form of sorted data
6 A table can contain only one cluster index
Non Cluster Index
1 A non cluster index is in the form of a report about the tables.
2 They are not created on the physical level but at the logical level
3 It does not sort the data at physical level
4 A table has 255 non clustered indexes
5 A table has many non clustered indexes.
6 It work on the order of data
Clustered Index
Only one per table
Faster to read than non clustered as data is physically stored in
index order
Non Clustered Index
Can be used many times per table
Quicker for insert and update operations than a clustered index
Both types of index will improve performance when select data with fields that use the index but will slow down update and insert operations.
The difference is that, Clustered index is unique for any given table and we can have only one clustered index on a table. The leaf level of a clustered index is the actual data and the data is resorted in case of clustered index.
Whereas in non-clustered index the leaf level is actually a pointer to the data in rows so we can have as many non-clustered indexes as we can on the database.
The difference of cluster index and non cluster index is:
Cluster index has only one column in the table, and slow when insert, update, and it searches one by one for each column.
Non cluster index its process is faster than when they are insert or update and it searches only an id not for each column of table.
Indexes are used to speed-up query process in SQL Server, resulting in high performance. They are similar to textbook indexes. In textbooks, if you need to go to a particular chapter, you go to the index, find the page number of the chapter and go directly to that page. Without indexes, the process of finding your desired chapter would have been very slow.
The same applies to indexes in databases. Without indexes, a DBMS has to go through all the records in the table in order to retrieve the desired results. This process is called table-scanning and is extremely slow. On the other hand, if you create indexes, the database goes to that index first and then retrieves the corresponding table records directly.
There are two types of Indexes in SQL Server:
Clustered Index
Non-Clustered Index
Clustered Index
A clustered index defines the order in which data is physically stored in a table. Table data can be sorted in only way, therefore, there can be only one clustered index per table. In SQL Server, the primary key constraint automatically creates a clustered index on that particular column.
Non-Clustered Indexes
A non-clustered index doesn’t sort the physical data inside the table. In fact, a non-clustered index is stored at one place and table data is stored in another place. This is similar to a textbook where the book content is located in one place and the index is located in another. This allows for more than one non-clustered index per table.
Please use the link to read complete info