SAP HANA is an in-memory database.
SAP HANA is one of the fastest growing products in SAP history and is viewed by the industry as a breakthrough solution for in-memory databases. SAP HANA claims that it accelerates analytics and applications on a single, in-memory platform, as well as combining databases, data processing, and application platform capabilities.
SAP HANA is the next-generation business platform that brings together:
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SAP HANA Studio runs on the Eclipse platform 3.6. We can use SAP HANA Studio on the following platforms:
Note: For Mac OS, HANA Studio is available, but there is no HANA client for that.
They are all the same, and 1.0 SP03 is touted to be the final name that should go into Ramp Up (beta) in Q4 2011. This allows any SAP NetWeaver BW 7.3 Data Warehouse to be migrated into a HANA appliance. HANA 1.0 SP03 specifically accelerates BW calculations and planning, which means that even more performance results can be attained.
Restricted users are those users who access the HANA system with some applications, but they don’t have SQL privileges on the HANA system. When these users are created, they don’t have the access initially.
If we compare restricted users with standard users:
A database schema is a way to logically group objects such as tables, views, stored procedures, etc. There are three types of schemas.
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The maximum number of tables in a schema in SAP HANA is 131,072.
The maximum number of columns in a HANA Table is 1,000.
Schema mapping is done when the physical schema in the target system is not the same as the physical schema in the source system.
Suppose, we are moving components from the development system (DEV) to the production system (PROD). The tables in DEV reside in DEV_SCHEMA and the same tables should reside in the PROD system in PROD_SCHEMA. If an Attribute View is transported from DEV to PROD, it will not work because the schema name is referenced in the definition of the Attribute View. In order for the promoted objects to work in PROD, schema mapping needs to be set-up in the target system.
Note: Schema mapping only applies to references from repository objects to catalog objects. It is not intended to be used for repository-to-repository references.
Delivery Unit (DU) is a container used by the Life Cycle Manager (LCM) to transport repository objects between the SAP HANA systems. The name of the Delivery Unit must contain only capital letters (A–Z), digits (0–9), and underscore (_).
In order to load data from external sources to SAP HANA, we need to establish a connection with the server. To connect, we need to provide the details of the Business Objects Data Services repository and ODBC drivers. Once the connection is established, we can import the table definition and then load data into the table definition.
SAP HANA 1.0 is an analytics appliance that consists of certified hardware, an in-memory database (IMDB), an analytics engine, and some tooling for getting data in and out of HANA. The logic and structures are built by the user and a tool is used, e.g., SAP Business Objects, to visualize or analyze data.
We need to import the tables T006 and T006A for Unit of Measures.
HANA supports both types of data stores in the database. A row store is used when we need to use the Select statement and no aggregations are performed.
A column store is used to perform aggregations, and HANA Modeling is supported only on column-based tables.
The only operating system that is supported by HANA is Suse Linux Enterprise Server SP1/SP2 (SLES SP1/2).
The supported object types in Modeler perspective are Attribute Views, Analytic Views, Calculation Views, Analytical Privileges, Procedures, Decision Tables, and Process Visibility Scenario.
The main SAP HANA database component is Index Server that consists of actual data engines for data processing, including input SQL and MDX statements, and performs authentic transactions.
Using the columnar data storage approach, the workload in SAP HANA is divided vertically. The columnar approach allows linear searching and aggregation of data unlike the two-dimensional data structure. If more than one column is to be processed, then each task is assigned to a separate processor. Operations on one column are then collimated by column divisions processed by different processors.
No, because a HANA database supports compression.
It is a set of SQL extensions for SAP HANA database that allows developers to push data-intensive logic into the database.
SQL Script should be used in cases where other modeling constructs of HANA, such as Attribute Views or Analytic Views, are not sufficient.
We can choose to associate an attribute with another attribute description. Label mapping is also called Description mapping. For example, if A1 has a label column B1, then we can rename B1 to A1.description. The related columns appear side by side during data preview.
A Join clause combines records from two or more tables/views in a database. SAP HANA supports the following types of Joins.
Analytic Privileges restrict users to view data for which they authorize. SAP HANA Analytic Privileges are used for security purposes. They are used to provide authorization on Attribute Views, Analytic Views, and Calculation Views.
Although SQL Privileges provide authorization at the object level, they do not provide authorization at the record level, so to provide both record-level and object-level authorizations SAP HANA Analytic Privileges can be used.
An attribute represents the descriptive data used in modeling, e.g., city, country, etc.
An Attribute View is used to model an entity based on the relationship between the attribute data that resides in multiple source tables. We can model columns, calculated columns, and hierarchies.
Join Engine is used to create an Attribute View.
Calculated attributes are derived from one or more existing attributes or constants, e.g., deriving the full name of a customer (both first name and last name). It is a read-only field, the value of which is calculated based on a specified formula.
SAP HANA Calculation View is a powerful information view.
SAP HANA Analytic View measure can be selected from only one fact table. When there is a need for more fact tables in the information view, then Calculation View comes into the picture.
The different types of nodes in a Calculation View are:
Calculation View with Star Join does not allow base Column tables, Attribute Views, or Analytic views to get added at Data Foundation. All Dimension tables must be changed to Dimension Calculation Views to be used in Star Join. All Fact tables can be added and they can use default nodes in Calculation View.
Yes. We can call all views (Attribute Views, Analytic Views, and other Calculation Views, as well as tables) inside a Calculation View. Calculation Views are composite views that can be used to combine other views.
SQL Engine is used to create a Calculation View.
Analytic View is in the form of a star schema, wherein we join one Fact table to multiple Dimension tables. Analytic Views use the real power of SAP HANA to perform complex calculations and aggregate functions by joining tables in the form of a star schema and by executing star schema queries.
Following are the properties of SAP HANA Analytic Views:
Star Join in an Analytic View joins the Attribute View to the Fact table to create a star schema structure, i.e., one central Transaction Data table being surrounded by multiple Master Data tables. It consumes the Fact table forwarded to it from the Data Foundation node and accepts Attribute Views in it. The output columns chosen after creating the Join are forwarded to the Semantics layer. The output table is then made available to the end-user for data analysis.
OLAP Engine is used to create an Analytic View.
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