Indexes- Best Practices for SAP HANA

2160391 – FAQ: SAP HANA Indexes SEPTEMBER 17, 2015 BY SAP HANA WIKI0 COMMENTS 1. What are SAP HANA indexes in the context of this SAP Note? SAP HANA indexes in the context of this SAP Note are data structures on tables, that can provide efficient table data access and / or guarantee uniqueness. This index concept is very common for relational databases. In general the term “index” in SAP HANA can also mean “table” or “data”. For example, the main SAP HANA process “indexserver” obviously works on data in the first place and not on indexes.

2. What is the purpose of indexes in SAP HANA environments? The main reasons for creating indexes in SAP HANA environments are: 

Efficient table data access (see SAP Note 2000002)



Efficient support of unique and primary key constraints

3. Which special aspects and limitations have to be considered with indexes? For an efficient index design it is good to know the following aspects and limitations of indexes: Scenario

Details

Although the index (and the underlying dictionary) provides sorted data, it is not possible to retrieve the minimum or the maximum value directly. Instead the whole data has to be No support of MIN scanned to find the minimum / maximum. Main reason for this and MAX technical restriction is the fact that two separate data areas exist (main and delta storage) and so no globally sorted data set is available.

No support of ORDER BY

Although the index (and the underlying dictionary) provides sorted data, it is not possible to support an ORDER BY with an index. Instead always an explicit sorting needs to be done. Main reason for this technical restriction is the fact that two separate data areas exist (main and delta storage) and so no globally sorted data set is available.

Risk of performance regressions with INVERTED HASH indexes

Hash collisions or range conditions on index columns can result in performance regressions when using INVERTED HASH indexes. See SAP Note 2109355 for more details.

Increased Due to the fuzzy content of FULLTEXT indexes the memory memory requirements can be significantly higher than for normal requirements of indexes. FULLTEXT indexes Indexes on For technical reasons indexes on columns with PREFIXED or PREFIXED and SPARSE compression may not be used for efficient data access. SPARSE columns See SAP Note 2000002 for more information. may not be used

Implicit indexes when creating primary key

When a unique or primary index is created on multiple columns of a column store table, an (unnamed) implicit single column index is created on all individual columns. If for example a primary key is created on columns MANDT, BELNR and POSNR, implicit single column indexes are created on column MANDT, on column BELNR and on column POSNR.

4. Where can I find information about existing indexes? Information about indexes is available in the following SAP HANA tables and monitoring views: Table name

Details

FULLTEXT_INDEXES

Fulltext indexes

GEOCODE_INDEXES

Geocode indexes

INDEXES

All existing indexes

INDEX_COLUMNS

Columns of all existing indexes

M_CS_INDEXES

Column store indexes

M_FUZZY_SEARCH_INDEXES

Fuzzy search indexes

M_RS_INDEXES

Row store indexes

The following index related SQL statements are available via SAP Note 1969700: SQL statement

Details

SQL: “HANA_Indexes_Columns”

Index columns

Shows single column indexes on columns with SPARSE or SQL: PREFIXED compression type “HANA_Indexes_ColumnStore_IndexesOnSparseAndPref (which may not provide xedColumns” performance benefit, see SAP Note 2000002 for more information) Shows redundant single column indexes (which are SQL: “HANA_Indexes_ColumnStore_RedundantIndexes” already implicitly created on columns of primary key or unique indexes)

SQL: “HANA_Indexes_HashCollisions”

Hash collisions of INVERTED HASH indexes (SAP Note2109355)

SQL: “HANA_Indexes_LargestIndexes”

Overview of largest indexes

SQL: “HANA_RowStore_TotalIndexSize”

Calculation of total row store index size and comparison with Pool/RowEngine/CpbTree heap allocator in order to detect memory leak

5. What kind of indexes exist in SAP HANA environments? The following indexes are available in SAP HANA environments: Store Index type Row store

BTREE [UNIQUE]

Row store

CPBTREE [UNIQUE]

Column FULLTEXT store Column INVERTED store HASH [UNIQUE]

SAP Note

Details

Creation command

B*tree index on row store table

CREATE [UNIQUE] BTREE INDEX ...

21126 B*tree index with compressed prefix CREATE [UNIQUE] 04 on row store table CPBTREE INDEX ... Fulltext index

CREATE FULLTEXT INDEX ...

21093 INVERTED HASH index, more CREATE [UNIQUE] 55 memory efficient alternative INVERTED HASH to INVERTED VALUE indexes INDEX... Maps column dictionary value IDs to

row IDs, no B*tree structure

INVERTED VALUE index, standard column store index that maps value CREATE [UNIQUE] IDs of dictionary to row IDs of INVERTED VALUE column INDEX ... Maps column dictionary value IDs to row IDs, no B*tree structure

INVERTED Column VALUE store [UNIQUE]

6. Which general recommendations exist for individually created indexes? The following general recommendations should be considered when creating indexes individually: Recommendation Details

As few indexes as possible

Every index imposes overhead in terms of space and performance, so you should create as few indexes as possible.

As small indexes as Specify as few columns as possible in an index, so that the space possible overhead is minimized.

Single column indexes in column store have much less space overhead, because they are implemented as rather small additional column data structure. Therefore you should use Prefer single column single column indexes whenever possible. indexes in column Due to the in-memory approach it is typically fine to define an store index only on the most selective column in SAP HANA environments, while on other relational databases often only a multi-column index provides optimal performance.

7. Are there tools available which automatically suggest useful indexes? While the individual design of secondary indexes is typically an outcome of SQL optimization there are already the following general approaches available to determine useful secondary indexes: Area

Details

SAP Suite on See SAP Note 1794297 that provides some reports for identifying useful

HANA

indexes.

SAP Bank Analyzer

See SAP Note 2015986 for general suggestions on index design in Bank Analyzer environments.

General

$DIR_INSTANCE/exe/python_support/indexAdvisor.py is a Python script that identifies useful indexes.

8. Which DDL operations can be performed on indexes? Important DDL operations on indexes are: Operati Command on Create CREATE ... INDEX "" ON "" ... Drop

DROP INDEX "" ALTER INDEX "" REBUILD

Rebuild Only relevant for row store, as column store indexes are automatically rebuilt during delta merge operations. Rename RENAME INDEX "" TO "" 9. How are indexes stored in column store? Single-column indexes in column store are rather light-weight data structures on top of the column structure, so called inverted indexes. Multi-column indexes in column store are stored as internal columns, so called CONCAT attributes. See SAP Note 1986747 for more information how multi-column indexes are stored as internal columns. On a CONCAT attribute columns also an inverted index is created, just like for columns being used by a single-column index. 10. Are indexes persisted to disk? The following overview shows which kind of indexes are persisted to disk: Store

Index type

Multi Column column store indexes

SP Detail S = 07 attributes.ini -> [global] -> runtime_structure_persiste true nce

If set to ‘true’ CONCAT attributes are persisted to disk (increased disk space requirements, but quicker load times). If set to ‘false’ CONCAT attributes are not persisted to disk and recreated during column load (less disk space requirements, but slower load times). SAP Note1976994 describes a wrong result set bug with Rev. 70 caused by persisted indexes.

Single Column column store indexes

Only maintained in memory, recreated during column load

Row store

Only maintained in memory, recreated during startup

11. Why do I need single column indexes on column store tables although the column dictionary is already sorted? The column dictionary contains the existing column values in a sorted way, but it doesn’t contain the information, in which rows of the table a certain value exists. This mapping from the dictionary value ID to the related table row IDs is only available via an index (“inverted index”). Without index, the whole column has to be scanned for a specific value. The following picture illustrates the direct mapping of dictionary value IDs to table row IDs via an inverted index (right hand side):

12. Where can I see if an indexes is used by a certain SQL statement? This information is available via PlanViz (see SAP Note 2073964). Example: (inverted index on column X used for access)

13. Are indexes dedicated storage objects? On other databases administrators are used to consider indexes as dedicated storage objects like segments (e.g. DBA_SEGMENTS entries with SEGMENT_TYPE = ‘INDEX’ on Oracle). This doesn’t apply for SAP HANA. As already seen above, indexes are extensions to column structures (inverted indexes) or internal columns (e.g. CONCAT attributes, TREX external key, see SAP Note1986747), and the allocated space is in the first place purely linked to the underlying table. Only with specific analysis tools like SQL: “HANA_Tables_LargestTables” or SQL: “HANA_Indexes_LargestIndexes” (SAP Note1969700) it is possible to understand better how much space is allocated by index structure.