SAP HANA Interview Questions and Answers

SAP HANA is an in-memory computing engine (IMCE) used for real-time processing of huge volumes of data and building and deploying real-world applications. Adopting the row-based and column-based DB technology, SAP HANA is an advanced relational DB product serviced by SAP SE. With this high-performance analytic (HANA) system, the big data exists on the main memory and not on the hard disk. It replaces the onus of data maintenance separately on the legacy system and simplifies the tasks of administrators in this digital world.

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Name the operating system SAP HANA supports.

More than 70% of customers run their SAP workloads on Linux with the use of SUSE Linux Enterprise Server, which is the best OS choice for SAP HANA.

Using the columnar data storage approach, the workload in SAP HANA is divided vertically. The columnar approach allows linear searching and aggregation of data rather than two-dimensional data structure. If more than one column is to be processed, each task is assigned to diverse processor. Operations on one column are then collimated by column divisions processed by different processors.

• With the HANA technology, you can create gen-next applications giving effective and efficient results in the digital economy.
• By using singe data-in memory, SAP HANA supports smooth transaction process and fault-tolerant analytics
• Easy and simple operations using an open-source, unified platform in the cloud
• High-level Data Integration to access massive amounts of data
• Advanced tools for in-depth analysis of present, past and the future.

List the merits and demerits of using row-based tables.

Merits:

• No data approach can be faster than row-based if you want to analyze, process and retrieve one record at one time.
• Row-based tables are useful when there is specific demand of accessing complete record.
• It is preferred when the table consists of less number of rows.
• This data storage and processing approach is easier and effective without any aggregations and fast searching.

Demerits:

• The data retrieval and processing operations involve the complete row, even though all the information is not useful.

• Allows smoother parallel processing of data as the data in columns is stored vertically. Thus, to access data from multiple columns, every operation can be allocated to a separate processor core.
• Only specific columns need to be approached for Select query and any column can be used for indexing.
• Efficient operations since most columns hold unique values and thus, high compression rate.

Since analytic applications require massive aggregations and agile data processing, column-based tables are preferred in SAP HANA as the data in column is stored consequently, one after the other enabling faster and easier readability and retrieval. Thus, columnar storage is preferred on most OLAP (SQL) queries. On the contrary, row-based tables force users to read and access all the information in a row, even though you require data from few and/or specific columns.

Index Server consists of actual data engines for data processing including input SQL and MDX statements and performs authentic transactions.

The persistence layer in SAP HANA handles all logging operations and transactions for secured backup and data restoring. This layer manages data stored in both rows and columns and provides steady save points. Built on the concept of persistence layer of SAP’s relational database, it ensures successful data restores.

Besides managing log data on the disk, HANA’s persistence layer allows read and write data operations via all storage interfaces.

Modeling Studio is an operational tool in SAP HANA based on Eclipse development and administration, which includes live project creation.

• The SAP HANA Studio further builds development objects and deploys them, to access and modify data models like HTML and JavaScript files.
• It also handles various data services to perform data input from SAP warehouse and other related databases.
• Responsible for scheduling data replication tasks.

• Run-length encoding
• Cluster encoding
• Dictionary encoding

SLT expands to SAP Landscape Transformation referring to trigger –based replication. SLT replication permits data transfer from source to target, where the source can be SAP or non-SAP while the target system has to be SAP HANA with HANA database. Users can accomplish data replication from multiple sources.

The three replication techniques supported by HANA are:

1. SLT
2. SAP Business Objects Data Services (BODS)
3. SAP HANA Direct Extractor Connection (DXC)

• Master Job (IUUC_MONITOR_)
• Data Load Job (DTL_MT_DATA_LOAD__<2digits>)
• Master Controlling Job (IUCC_REPLIC_CNTR_)
• Migration Object Definition Job (IUCC_DEF_MIG_OBJ_<2digits>)
• Access Plan Calculation Job (ACC_PLAN_CALC__<2digits>)

The time duration to perform data replication starting from the source to the target system is known as latency.

• SAP HANA Studio
• SAP HANA Application Cloud
• SAP HANA Cloud
• Sap HANA DB

During a regular operation, data is by default stored to the disk at save points in SAPHANA. As soon as there is any update and transaction, logs become active and get saved from the disk memory. In case of power failure, the database restarts like any other DB returning to the last savepoint log state. SAP HANA requires backup to protect against disk failure and reset DB to the previous state. The backups simultaneously as the users keep performing their tasks.

Configuration is the meaningful information to establish a connection between source, SLT system and SAP HANA architecture as stated in the SLT system. Programmers are allowed to illustrate a new Configuration in Configuration and Monitoring Dashboard.

The waiting process for data to load from the main memory to the CPU cache is called Stall.

There are primarily three types of information views in SAP HANA, which are all non-materialized.

• Attribute view
• Analytic view
• Calculation View

They are SLT Replication Application Servers to provide configuration information for data replication. This replication status can also be monitored.

Logging table records all replicated changes in the table, which can be further replicated to the target system.

Using advanced replication settings, transformation rules are specified to transfer data from source tables during replication process. For instance, setting rules to covert fields, fill vacant fields and skip records. These rules are structured using advanced replication settings (transaction IUUC_REPL_CONT)

SAP HANA transaction manager synchronizes database transactions keeping the record of closed and open transactions. When a transaction is committed or rolled back, the manager informs all the active stores and engines about the action so that they can perform required actions in time.

Each SQL statement in SAP HANA is carried out in the form of a transaction. Every time, a new session is allocated to a new transaction.

A Master-controller job is responsible to build database logging table in the source system. It further creates synonyms and new entries in SLT server admin when the table loads / replicates.

Pause the replication process and terminate the schema-related jobs.

No

The number of data transfer jobs change when the initial loading speed or latency replication time is not up to the mark. At the end of the initial load, the number of initial load jobs may be reduced.