SAP HANA Interview questions

SAP HANA Interview Questions
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1. Define Five-minute rule?
It is a rule of thumb for deciding whether a data item
should be kept in memory, or stored on disk and read back
into memory when required. The rule is “randomly
accessed disk pages of cache are re-used every 5 minutes”.

2. Define multi-core CPU?
Multiple CPU’s on one chip or in one package is called
multi-core CPU.

3. Define Stall?
Waiting for data to be loaded from main memory into the
CPU cache is called as Stall.

4. What is SAP In-Memory Appliance (SAP
HANA)?
HANA is an in-memory technique to store data that is
particularly suited for handling very large amounts of
tabular, or relational, data with extra ordinary
performance. Common databases store tabular data rowwise. Reorganizing the data in memory column-wise brings
a tremendous speed increase when accessing a subset of
the data in each table row.

5. What are the components or products of
HANA?
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SAP HANA contains the following components.
SAP HANA DATABASE
SAP HANA Studio SAP HANA CLIENT
SAP HANA INFORMATION COMPOSER
DIAGNOSTIC AGENT 7.3
SAP HANA client package for MS excel
SAP HANA UI for Information Access (INA)
SAP HANA AFL 1.0
Software Update Manager for SAP HANA
SAP LT Replication Add On
SAP LT Replication Server
SAP HANA Direct Extractor Connection (DXC)
SAP Data Services 4.0

6. What are the different editions available in
HANA appliance software?
 Platform Edition:

Platform edition is intended for customers who want to use
ETL-based replication and already have a license for SAP
BO Data Services.
 Enterprise Edition:
Enterprise edition is intended for customers who want to
use either trigger-based replication or ETL-based
replication and do not already have all of the necessary
licenses for SAP BO Data Services.

7. What is columnar and Row-Based Data
Storage?
A database table contains data in the form of rows and
columns. However Computer memory is organized as a
linear structure. To store a table in linear memory, there are
two options. A row-based storage stores a table as a
sequence of records, each of which contains the fields of
one row. In a columnar storage the entries of a column are
stored in contiguous memory locations. The SAP HANA
database allows specifying whether a table is to be stored
column-wise or row-wise. It is also possible to alter an
existing table from columnar to row-based and vice versa.
Search operations in tabular data can be accelerated by
organizing data in columns instead in rows.

8. What are the advantages of Column based
tables?
 Calculations are typically executed on single or a few

columns only.
 The table is searched based on values of a few columns.
 The table has a large number of columns.
 The table has a large number of rows and columnar
operations are required (aggregate, scan, etc.).
 High compression rates can be achieved because the
majority of the columns contain only few distinct values
(compared to number of rows).

9. What are the advantages of Row-based tables?
 The application needs to only process a single record at
one time (many selects and/or updates of single records).
 The application typically needs to access a complete record
(or row).
 The columns contain mainly distinct values so that the
compression rate would be low.
 Neither aggregations nor fast searching are required.
 The table has a small number of rows (e. g. configuration
tables).

10. Which case the data to be stored in columnar
storage?
To enable fast on-the-fly aggregations, ad-hoc
reporting, and to benefit from compression mechanisms it
is recommended that transaction data to be stored in a
column-based table.

11. What is paralisation?
Column-based storage makes it easy to execute operations
in parallel using multiple processor cores. In a column store
data is already vertically partitioned means that operations
on different columns can easily be processed in parallel. If
multiple columns need to be searched or aggregated, each
of these operations can be assigned to a different processor
core. In addition operations on one column can be
parallelized by partitioning the column into multiple
sections that can be processed by different processor cores

12. What are the different Compression
Techniques?
1. Run-length encoding
2. Cluster encoding
3. Dictionary encoding

13. Why materialized aggregates are not
required?
With a scanning speed of several gigabytes per
millisecond, in-memory column stores, make it possible to
calculate aggregates on large amounts of data on the fly
with high performance. This is expected to eliminate the
need for materialized aggregates in many cases.

14. What are the advantages of Eliminating
materialized aggregates?
 Simplified data model
 Simplified application logic
 Higher level of concurrency and With the fly Aggregation

we have aggregated values up to date

15. What are the different types of replication
techniques?
 ETL based replication using BODS
 Trigger based replication using SLT
 Extractor based data acquisition using DXC

16. Define SLT?
SLT stands for SAP Landscape Transformation which is a
trigger based replication. SLT replication server is the
replication technology to pass data from source system to
the target system. The source can be either SAP or nonSAP. Target system is SAP HANA system which contains
HANA database.

17. What is Configuration in SLT?
The information to create the connection between the
source system, SLT system, and the SAP HANA system is
specified within the SLT system as a Configuration. You can
define a new configuration in Configuration & Monitoring
Dashboard (transaction LTR).

18. What is Configuration and Monitoring
Dashboard?
It is an application that runs on SLT replication server to
specify configuration information (such as source
system, target system, and relevant connections) so that
data can be replicated. It can also use it to monitor the
replication status (transaction LTR).
 Status Yellow: It may occur due to triggers which are not
yet created successfully.
 Status Red: It may occur if master job is aborted (manually
in transaction SM37).

19. What is advanced replication settings?
A transaction that runs on SLT replication server to specify
advanced replication settings like
a. Modifying target table structures,
b. Specifying performance optimization settings
c. Define transformation rules

20. Define Latency?
It is the length of time to replicate data (a table entry) from
the source system to the target system.

21. Define logging table?
A table in the source system that records any changes to a
table that is being replicated. This ensures that SLT
replication server can replicate these changes to the target
system.

22. What are Transformation rules?
A rule specified in the Advanced Replication settings
transaction for source tables such that data is transformed
during the replication process. Example you can specify
rule to
 Convert fields
 Fill empty fields
 Skip records

23. When to change the number of Data Transfer
job?
If the speed of the initial load/replication latency time is
not satisfactory If SLT replication server has more
resources than initially available, we can increase the
number of data transfer and/or initial load jobs. After the
completion of the initial load, we may want to reduce the
number of initial load jobs.

24. When to go for table partitioning?
If the table size in HANA database exceeds 2 billion
records, split the table by using portioning features by
using “Advanced replication settings” (transaction
IUUC_REPL_CONT, tab page IUUC_REPL_TABSTG).

25. What are the jobs involved in replication
process?
 Master Job (IUUC_MONITOR_<MT_ID>)
 Master Controlling Job (IUUC_REPLIC_CNTR_<MT_ID>)
 Data Load Job
(DTL_MT_DATA_LOAD_<MT_ID>_<2digits>)
 Migration Object Definition Job
(IUUC_DEF_MIG_OBJ_<2digits>)
 Access Plan Calculation Job
(ACC_PLAN_CALC_<MT_ID>_<2digits>)

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