Update on SAP HANA dynamic tiering enhancements.

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SAP HANA SPS 11 - What’s New?
SAP HANA dynamic tiering
SAP HANA Product Management December, 2015
(Delta from SPS 10 to SPS 11)

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Agenda
News in SAP HANA dynamic tiering
 Support for IBM Power Platform and more
Extended usage of SAP HANA dynamic tiering in SAP BW
 Higher impact on memory footprint with SAP BW 7.50
News in the Data Lifecycle Manager (DLM) of the SAP HANA Data Warehousing Foundation

3. SAP HANA dynamic tiering
News in SPS 11

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SAP HANA dynamic tiering - What’s New in SPS 11?
Data Center Readiness, Integration and Management
Support for the IBM Power Platform
 Starting with SPS 11, dynamic tiering is supported on SUSE Linux Enterprise Server 11 SP4 for IBM Power
operating system
New monitoring tiles in the SAP HANA cockpit
Intelligent data caching
Support for native data warehousing
Improvements for handling multi-dimensional data models involving extended tables
 Enhanced join relocation
 Optimized handling of dimension-joins to extended tables

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New Cockpit Tiles

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New HANA Dynamic Tiering Memory tile
 Dynamic tiering uses several types
of memory:
– Delta: in-memory delta store for row-
level updates
– Large / Load: used for bulk data loading
– Temp Cache: used for temp tables and
other structures that are transient
– Main Cache: used for static, persistent
user data
 Tile displays total allocated memory,
along with amount in use, and
amount still available
 You can change the amount of
allocated memory by clicking on
“Modify Allocation”
 The memory allocation for HANA
System cannot be changed

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New HANA Dynamic Tiering Connections tile
 View active and idle connections
 Click any row for connection
details
 If necessary, you can cancel a
connection
 You can also “Modify
Configuration” to change
properties of the DT server, such
as:
– Maximum number of concurrent
connections
– Number of threads

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Connection details...
Click “Active Transactions” or
“Remote Statements” to view
related details for the given
connection

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Cancelling a connection...

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Connection cancelled...

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Query performance improvement
Data management - intelligent data caching
Reporting Performance
 Query fragments containing join between in-
memory and extended tables are relocated
to DT to optimize data transfer
 DT will pull data from in-memory HANA host
each time a query needs it
 HANA tables will be cached in DT during
fetch, and then subsequently re-used
 Re-use based on sub-sumption (can cache
a subset of the table and use it)
 Merge subsets of cache or use a quota to
limit maximum caching
 Maintain cache coherency – invalidate
cache with updates to in-memory tables Hot Store
Fast data movement and optimized push down query processing
SAP HANA System with dynamic tiering service
Worker
host(*)
Worker
host
Worker
host
Client
Application
Connect
ES host
Column
Table
Row
Table
Extended
Table
Warm Store
Common Storage System (*) Standby hosts not shown
Column
TableColumn
Table
Row
TableRow
Table
Cache of
subset of
Column Table
Cache of
subset of
Column Table
Cache of
subset of
Column Table
T1 T2
Hot Warm
JOIN
T1 T2
Hot Warm
JOIN
Internally converted to

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SAP HANA Cockpit: customizing for intelligent data caching
Add new parameters to esserver.ini configuration file
You will need to add new configuration parameters for
intelligent data caching:
• ‘esserver.ini’ is the configuration file for the DT server
• Click on “Edit” button at bottom right of screen to delete
or modify existing entries in the esserver.ini file.
• There is also a ‘+’ sign at the top right of the screen to
set additional DT server configuration parameters
• Add these new entries to the esserver.ini file:
• result_cache_temp_pct (default 0)
• Sets the max size of cached results as a percent
of the temp cache size. Generally should be less
than 100% so that results are not paged out in
temp store.
• result_cache_max_result_pct (default 10)
• Prevent large tables that won’t fit in the result
cache from washing out smaller ones.

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Planned Innovations Future DirectionToday
This is the current state of planning and may be changed by SAP at any time.
SPS 11 – Q4 2015
Roadmap SAP HANA dynamic tiering
Summary
Technical integration
 Common installer
 Backup integration (file-based and Backint)
 Host auto-failover (local HA)
 Integrated admin & monitoring
 Intelligent data caching
 Power PC platform support
Functional integration and usage
 Integration in global database catalog
– New HANA table type “extended table”
 Cross-store optimizer
 Use extended tables in Calculation Models
 Multitenant database container support
 Support for extended tables in SAP BW
powered by SAP HANA (PSA+w/o DSO)
 Support for extended tables in major HANA-
related data provisioning technologies
Functional integration
• Data lifecycle management
– Enable use of DT in SAP S/4HANA
 Coverage of special SAP HANA features
– Text, spatial, and series data
– Improved handling of extended tables in
AFLs
Enterprise DB features
 SAP HANA system replication
 Multistore data management within a table
 DT scale out
Enterprise DB features
 SAP HANA system replication
Data management
 Delta backup mechanisms
 Persistence encryption

14. SAP BW powered by SAP HANA
Extended usage of dynamic tiering in SAP BW 7.50

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EDW Propagation
EDW Transformation
Future direction: SAP BW & dynamic tiering
Use extended tables in transformation and propagation layer
BW – Operational Data
Data Categories in a BW System
Staging Layer
Analytic Mart
Business Transformation
Corporate
Memory
EDW Propagation
EDW Transformation
Archive/NLS
Archived
Planned with next major BW release:
Use extended tables for „warm“ part of transformation and propagation layer (advanced DSOs only)

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PLANNED INNOVATIONS Future DirectionToday
This is the current state of planning and may be changed by SAP at any time.
(BW. 7.4 SP08 + HANA SPS 09) (BW 7.50) (mid- to long-term)
Future direction: SAP BW & dynamic tiering
Summary
 PSA
 Write-optimized DSO
 “advanced“ DSO (inbound table only)
Target:
 Staging area and corporate memory
 ~20% of BW data footprint
 All major “advanced” DSOs
– Full tables / providers only
– Data separation via simple
“data flow split”
Target:
 As before + „warm“ parts of
propagation & transformation layer
 ~40% of BW data footprint
 Optimizations of reporting/read
access for data in DT
 Optional integration of NLS storage
into dynamic tiering
Target:
 As before + „warm“ parts of
reporting layer
 Max. 70% of data footprint
Remark: SAP NLS with SAP IQ is not replaced by the BW integration of HANA dynamic tiering. NLS is a powerful and sophisticated archiving
solution. It is complementary to dynamic tiering and part of the multi-temperature data lifecycle management of BW. Depending on the scenarios,
data growth and architecture our customers have the option to use both “tiers” or just one.

17. Data Lifecycle Manager
Recent enhancements

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SAP Data Warehousing Foundation
Data Lifecycle Manager (DLM)
Define a data temperature management strategy with DLM – available with DWF 1.0 SP01
Leverage SAP HANA tables, SAP HANA Dynamic Tiering (Warm-Store), Hadoop or SAP Sybase IQ in SAP
HANA native use cases with a tool based approach to model aging rules on tables to displace ‘aged’ data to
optimize the memory footprint of data in SAP HANA.
SAP HANA
Data Lifecycle Manager
HOT-STORE
(Column Table)
WARM-STORE
(Extended Table)
DATA
MOVEMENT
Generated SAP HANA View (Pruning / UNION)

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DLM SPS03 - Supported Storage Destination Types
Storage Destination Type Restrictions
SAP HANA Dynamic Tiering Local The following factors prevent lifecycle profile from being activated:
•Source tables with keys of type
VARCHAR/CHAR/VARBINARY/BINARY and length greater than 255
•Source tables with keys of type NVARCHAR/NCHAR and length
greater than 85
•Source tables of type row
•Source tables with columns with data type BLOB
•Source tables without a primary key
SAP IQ over SDA
Spark SQL (DESTINATION) The following factors prevent the lifecycle profile from being activated:
•Source tables with columns with data type TEXT, SHORTTEXT,
BINTEXT, BLOB, CLOB, TIME, VARBINARY, NCLOB, or ALPHANUM
Deletion Bin Destination The following factors prevent the lifecycle profile from being activated:
•Source tables without a primary key

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DLM SPS03 - Manage Modeled Persistence Objects
Modeled persistence objects help you treat multiple source persistence objects, like tables, jointly in matters of data
relocation. You can define a source persistence object from multiple SAP HANA tables. Such a modeled persistence
object can be used in a lifecycle profile. The relocation rule in this case can be defined for common columns, which
have been selected during definition of the modeled persistence object.
Note: Modeled Persistence Objects are supported for storage destination types SAP IQ over SDA and SAP HANA
Dynamic Tiering.

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DLM SPS03 – Rule Editor: Manage Modeled Persistence Objects
When you create and execute a lifecycle profile for a
modeled persistence object, the following applies
for all tables of the modeled object:
A common relocation rule will be defined and
executed.
A common clash strategy and packet size applies.
A single relocation procedure will be generated.
For all tables corresponding target tables will be
generated.
An example for a modeled persistence object is a
table group. A table group is a set of SAP HANA
tables with common columns. Table groups are
supported for storage destination types SAP IQ over
SDA and SAP HANA Dynamic Tiering Local.

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DLM SPS03 – Import / Export of DLM Entities
Data Lifecycle Manager entities like storage destinations, modeled persistence objects, or
lifecycle profiles can be described in JSON format. For transport or backup purposes, you can
export and import the entities in JSON format.

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Future DirectionToday
SAP Data Warehousing Foundation
Product Roadmap Overview – Data Lifecycle Manager
Future innovations
• Pre-delivered Application DLM templates
• Support for multi-tiering
• Integrated lifecycle management
• Exploration module based on SQL Query Access
Cache
• Parallelization of relocation packet processing
• Support for CDS Entities as
source persistence object
• Expand call back targets for pruning node
substitution
Q4 / 2015
SAP DWH Foundation 1.0 SP03
• Support for Table Groups, Table Hierarchies
• Exploration module for Table Groups, Table
Hierarchies, additional exploration module type (drill
down) for HANA Table
• Automated substitution of data foundation in
Calculation Views (table replaced by generated view)
• Generate DLM profiles for a predefined set of tables
(table group)
• Option to exchange table-name with DLM generated
Pruning Node in existing HANA Calc-Views

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Where do I find more information on SAP HANA dynamic tiering?
Public Documentation:
http://help.sap.com/hana_platform
 Navigate to SAP HANA Options • SAP HANA Dynamic Tiering
 Covers only DT-specific information
i.e. add-on to SAP HANA platform documentation
Community information
Quick Start Guide
 https://scn.sap.com/docs/DOC-66016
Videos in the SAP HANA academy
 http://scn.sap.com/docs/DOC-59988

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