Latency is referred to the length of time to replicate data from the source system to the target system.
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.
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.
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.
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• By using single 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
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Logging table records all replicated changes in the table, which can be further replicated to the target system.
Modeling Studio is an operational tool in SAP HANA based on Eclipse development and administration, which includes live project creation.
• It also handles various data services to perform data input from SAP warehouse and other related databases.
• Responsible for scheduling data replication tasks.
The transaction manager co-ordinates database transactions and keeps a record of running and closed transactions. When transaction is rolled back or committed, the transaction manager notifies the involved storage engines about the event so they can run necessary actions.
The job is arranged on demand and is responsible for
There are three different compression techniques
In the HANA database, each SQL statement is implemented in the reference of the transaction. New session is allotted to a new transaction.
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.
• 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.
Pause the replication process and terminate the schema-related jobs.
There are primarily three types of information views in SAP HANA, which are all non-materialized.
• Attribute view
• Analytic view
• Calculation View
• Run-length encoding
• Cluster encoding
• Dictionary encoding
To avoid un-necessary information from being stored, you have to pause the replication by stopping the schema-related jobs
Modeling studio in HANA performs multiple task like
• SAP HANA Studio
• SAP HANA Application Cloud
• SAP HANA Cloud
• Sap HANA DB The Sap Hana Training Videos and Certification Course can open the doors to a stellar career for you.
During a regular operation, data is by default stored to the disk at savepoints in SAPHANA. As soon a 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.
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 has an in-memory computing engine and access the data straightaway without any backup. To avoid the risk of losing data in case of hardware failure or power cutoff, persistence layer comes as a savior and stores all the data in the hard drive which is not volatile.
You can avoid un-necessary logging information from being stored by pausing the replication by stopping the schema-related jobs.
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 savepoints. 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.
The two types of relational data stored in HANA includes
They are SLT Replication Application Servers to provide configuration information for data replication. This replication status can also be monitored.
SAP HANA stands for High Performance Analytical Appliance- in-memory computing engine. HANA is linked to ERP systems; Frontend modeling studio can be used for replication server management and load control.
• 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.
If the replication is suspended for a longer period of time, the size of the logging tables increases.
Transformation rule is the rule specified in the advanced replication setting transaction for the source table such that data is transformed during the replication process.
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.
SAP HANA DB
SAP HANA Studio
SAP HANA Appliance
SAP HANA Application Cloud
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:
• SAP Business Objects Data Services (BODS)
• SAP HANA Direct Extractor Connection (DXC)
Index Server 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 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.
The time duration to perform data replication starting from the source to the target system is known as latency.
The waiting process for data to load from the main memory to the CPU cache is called Stall.
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.