VENKAT SAP HANA

SAP HANA database persistence layer is responsible to manage logs for all the transactions to provide standard data back up and system restore function.

It ensures that database can be restored to the most recent committed state after a restart or after a system crash and transactions are executed completely or completely undone. SAP HANA Persistent Layer is part of Index server and it has data and transaction log volumes for HANA system and in-memory data is regularly saved to these volumes. There are services in HANA system that has their own persistence. It also provides save points and logs for all the database transactions from the last save point.

Why does SAP HANA database need a Persistent Layer?

Main memory is volatile therefore data is lost during a restart or power outage.
Data needs to be stored in persisted medium.
Backup & Restore is available.
It ensures that the database is restored to the most recent committed state after a restart and that transaction are either completely executed or completely undone.

Data and Transaction Log Volumes

Database can always be restored to its most recent state, to ensure these changes to data in the database are regularly copied to disk. Log files containing data changes and certain transaction events are also saved regularly to disk. Data and logs of a system are stored in Log volumes.

Data volumes stores SQL data and undo log information and also SAP HANA information modeling data. This information is stored in data pages, which are called Blocks. These blocks are written to data volumes at regular time interval, which is known as save point.

Log volumes store the information about data changes. Changes that are made between two log points are written to Log volumes and called log entries. They are saved to log buffer when transaction is committed.

Savepoints

In SAP HANA database, changed data is automatically saved from memory to disk. These regular intervals are called savepoints and by default they are set to occur every five minutes. Persistence Layer in SAP HANA database performs these savepoint at regular interval. During this operation changed data is written to disk and redo logs are also saved to disk as well.

The data belonging to a Savepoint tells consistent state of the data on disk and remains there until the next savepoint operation has completed. Redo log entries are written to the log volumes for all changes to persistent data. In the event of a database restart, data from the last completed savepoint can be read from the data volumes, and redo log entries written to the log volumes.

Frequency of savepoint can be configured by global.ini file. Savepoints can be initiated by other operations like database shut down or system restart. You can also run savepoint by executing the below command −

ALTER System SAVEPOINT

To save data and redo logs to log volumes, you should ensure that there is enough disk space available to capture these, otherwise the system will issue a disk full event and database will stop working.

During the HANA system installation, following default directories are created as the storage location for data and log volumes −

/usr/sap/<SID>/SYS/global/hdb/data
/usr/sap/<SID>/SYS/global/hdb/log

These directories are defined in global.ini file and can be changed at later stage.

Note that Savepoints do not affect the performance of transactions executed in HANA system. During a savepoint operation, transactions continue to run as normal. With HANA system running on proper hardware, impact of savepoints on the performance of system is negligible.

SAP HANA alert monitoring is used to monitor the status of system resources and services that are running in the HANA system. Alert monitoring is used to handle critical alerts like CPU usage, disk full, FS reaching threshold, etc. The monitoring component of HANA system continuously collects information about health, usage and performance of all the components of HANA database. It raises an alert when any of the component breaches the set threshold value.

The priority of alert raised in HANA system tells the criticality of problem and it depends on the check that is performed on the component. Example − If CPU usage is 80%, a low priority alert will be raised. However, if it reaches 96%, system will raise a high priority alert.

The System Monitor is the most common way to monitor HANA system and to verify the availability of all your SAP HANA system components. System monitor is used to check all key component and services of a HANA system.

You can also drill down into details of an individual system in Administration Editor. It tells about Data Disk, Log disk, Trace Disk, alerts on resource usage with priority.

Alert tab in Administrator editor is used to check the current and all alerts in HANA system.

It also tells about the time when an alert is raised, description of the alert, priority of the alert, etc.

SAP HANA monitoring dashboard tells the key aspects of system health and configuration −

High and Medium priority alerts.
Memory and CPU usage
Data backups

MDX Provider is used to connect MS Excel to SAP HANA database system. It provides driver to connect HANA system to Excel and is further, used for data modelling. You can use Microsoft Office Excel 2010/2013 for connectivity with HANA for both 32 bit and 64 bit Windows.

SAP HANA supports both query languages − SQL and MDX. Both languages can be used: JDBC and ODBC for SQL and ODBO is used for MDX processing. Excel Pivot tables use MDX as query language to read data from SAP HANA system. MDX is defined as part of ODBO (OLE DB for OLAP) specification from Microsoft and is used for data selections, calculations and layout. MDX supports multidimensional data model and support reporting and Analysis requirement.

MDX provider enables the consumption of Information views defined in HANA studio by SAP and non-SAP reporting tools. Existing physical tables and schemas presents the data foundation for Information models.

Once you choose SAP HANA MDX provider from the list of data source you want to connect, pass HANA system details like host name, instance number, user name and password.

Once the connection is successful, you can choose Package name → HANA Modeling views to generate Pivot tables.

MDX is tightly integrated into HANA database. Connection and Session management of HANA database handles statements that are executed by HANA. When these statements are executed, they are parsed by MDX interface and a calculation model is generated for each MDX statement. This calculation model creates an execution plan that generates standard results for MDX. These results are directly consumed by OLAP clients.

To make MDX connection to HANA database, HANA client tools are required. You can download this client tool from SAP market place. Once installation of HANA client is done, you will see the option of SAP HANA MDX provider in the list of data source in MS Excel.

Open SAP HANA Studio → Create Schema under Catalog tab. <Start here>

Prepare the data and save it to csv format. Now create file with “ctl” extension with following syntax −

---------------------------------------
import data into table Schema."Table name"
from 'file.csv'
records delimited by '\n'
fields delimited by ','
Optionally enclosed by '"'
error log 'table.err'
-----------------------------------------

Transfer this “ctl” file to the FTP and execute this file to import the data −

import from ‘table.ctl’

Check data in table by going to HANA Studio → Catalog → Schema → Tables → View Content

Direct Extractor Connection data replication reuses existing extraction, transformation, and load mechanism built into SAP Business Suite systems via a simple HTTP(S) connection to SAP HANA. It is a batch-driven data replication technique. It is considered as method for extraction, transformation, and load with limited capabilities for data extraction.

DXC is a batch driven process and data extraction using DXC at certain interval is enough in many cases. You can set an interval when batch job executes example: every 20 minutes and in most of cases it is sufficient to extract data using these batch jobs at certain time intervals.

Advantages of DXC Data Replication

This method requires no additional server or application in the SAP HANA system landscape.
DXC method reduces complexity of data modeling in SAP HANA as data sends to HANA after applying all business extractor logics in Source System.
It speeds up the time lines for SAP HANA implementation project
It provides semantically rich data from SAP Business Suite to SAP HANA
It reuses existing proprietary extraction, transformation, and load mechanism built into SAP business Suite systems over a simple HTTP(S) connection to SAP HANA.

Limitations of DXC Data Replication

Data Source must have a predefined mechanism for extraction, transformation and load and if not we need to define one.
It requires a Business Suite System based on Net Weaver 7.0 or higher with at least below SP: Release 700 SAPKW70021 (SP stack 19, from Nov 2008).

Configuring DXC Data Replication

Enabling XS Engine service in Configuration tab in HANA Studio − Go to Administrator tab in HANA studio of system. Go to Configuration → xsengine.ini and set instance value to 1.

Enabling ICM Web Dispatcher service in HANA Studio − Go to Configuration → webdispatcher.ini and set instance value to 1.

It enables ICM Web Dispatcher service in HANA system. Web dispatcher uses ICM method for data read and loading in HANA system.

Setup SAP HANA Direct Extractor Connection − Download the DXC delivery unit into SAP HANA. You can import the unit in the location /usr/sap/HDB/SYS/global/hdb/content.

Import the unit using Import Dialog in SAP HANA Content Node → Configure XS Application server to utilize the DXC → Change the application_container value to libxsdxc

Creating a HTTP connection in SAP BW − Now we need to create http connection in SAP BW using transaction code SM59.

Input Parameters − Enter Name of RFC Connection, HANA Host Name and <Instance Number>

In Log on Security Tab, enter the DXC user created in HANA studio using basic Authentication method −

Setting up BW Parameters for HANA − Need to Setup the Following Parameters in BW Using transaction SE 38. Parameters List −

PSA_TO_HDB_DESTINATION − we need to mention where we need to move the Incoming data (Connection Name created using SM 59)
PSA_TO_HDB_SCHEMA − To which Schema the replicated data need to assign
PSA_TO_HDB − GLOBAL To Replicate All data source to HANA. SYSTEM – Specified clients to Use DXC. DATASOURCE – Only Specified Data Source are used for
PSA_TO_HDB_DATASOURCETABLE − Need to Give the Table name having the List of data sources which are used for DXC.

Data Source Replication

Install data source in ECC using RSA5.

Replicate the metadata using specified application component (data source version Need to 7.0, if we have 3.5 version data source we need to migrate that. Active the data Source in SAP BW. Once data source is activated in SAP BW it will create the following Table in Defined schema −

/BIC/A<data source>00 – IMDSO Active Table
/BIC/A<data source>40 –IMDSO Activation Queue
/BIC/A<data source>70 – Record Mode Handling Table
/BIC/A<data source>80 – Request and Packet ID information Table
/BIC/A<data source>A0 – Request Timestamp Table
RSODSO_IMOLOG - IMDSO related table. Stores information about all data sources related to DXC.

Now data is successfully loaded into Table /BIC/A0FI_AA_2000 once it is activated.

This is also known as Sybase Replication in HANA system. The main components of this replication method are the Sybase Replication Agent, which is part of the SAP source application system, Replication agent and the Sybase Replication Server that is to be implemented in SAP HANA system.

Initial Load in Sybase Replication method is initiated by Load Controller and triggered by the administrator, in SAP HANA. It informs R3 Load to transfer initial load to HANA database. The R3 load on source system exports data for selected tables in source system and transfer this data to R3 load components in HANA system. R3 load on target system imports data into SAP HANA database.

SAP Host agent manages the authentication between the source system and target system, which is part of the source system. The Sybase Replication agent detects any data changes at time of initial load and ensures every single change is completed. When th ere is a change, update, and delete in entries of a table in source system, a table log is created. This table log moves data from source system to HANA database.

Delta Replication after Initial Load

The delta replication captures the data changes in source system in real time once the initial load and replication is completed. All further changes in source system are captured and replicated from source system to HANA database using above-mentioned method.

This method was part of initial offering for SAP HANA replication, but not positioned/supported anymore due to licensing issues and complexity and also SLT provides the same features.

Note − This method only supports SAP ERP system as data source and DB2 as database.