The majority of the columns contain few distinct values compared to the number of rows.The table has a large number of records, and mostly columnar operations are required (aggregate, scan, etc).The table has a large number of columns.The table is searched based on values of a few columns.The calculation is typically executed on single or few columns only.On the other hand, in a columnar layout, the values of This row-based layout, all attributes of a tuple are stored consecutively and Columnar Data Organization in SAP HANA Database Let’s take an example to understand this concept.
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To store the data in memory, the database storage layer has to decide how to map the two-dimensional table structures to the linear memory address space.Īlso read: Layers in SAP Software Application The main memory, however, is a single-dimensional space, providing a memory address that starts at zero and increases serially to the highest available location. A table is a set of data elements organized in terms of vertical columns or attributes, (which are identified by their name) and horizontal rows or records. Relational databases represent data in two-dimensional structures called tables. Know More:- SAP Controlling Training Columnar Data Organization To achieve this goal in an efficient way, the persistence layer uses a combination of write-ahead logs, shadow paging, and data save points. SAP HANA ensures that changes are durable and that the database can be restored to the most recent committed state after a restart. Database technology ensures that database transactions are processed reliably and are not liable to external disruptions. In this context, we refer to a set of properties known as atomicity, consistency, isolation, and durability (ACID). It loses its content when it is out of power. Keeping data in SAP HANA Database In-Memory, raise a number of questions, first, what happens if there is a power outage? The main memory is volatile storage. Compared with accessing data on hard disks, typically data in the main memory can be accessed more than 100,000 times faster.Ĭompared with traditional RDBMS, which employs disks as the primary data store and uses main memory as a buffer for data processing, keeping data in memory can improve database performance just by advantage in access time. In the SAP HANA Database, the main memory is the first level of storage, next to CPU caches and it is directly accessible. To overcome this drawback, SAP HANA introduces the concept of delta store. Write operations, particularly inserts and updates to a columnar store, are more complicated and less efficient. The advantages of the columnar store for fast read performance have their price.
The optimization includes partitioning the data into sections for which the calculations can be executed in parallel.
This model allows parallel execution and scales incredibly well with the number of cores. To take advantage of massively parallel multi-core processors, SAP HANA Database manages the SQL processing instructions into an optimized model. Modern computer systems have a continuously increasing number of processing cores. SAP HANA resolves this by using columnar storage and effective data compression techniques to effectively reduce the overall size of data in memory and achieve high hit ratios in the different caching layers of the CPU. Additionally, the data movement between the CPU cache and main memory becomes the new performance bottleneck. With HANA Migration, all data is readily available in the main memory of the SAP HANA Database. Learn About: SAP Simple Finance Training Optimize In-Memory Data access Not only it is the slowest medium, but also (because there are typically four layers between the hard disk and CPU register. Because they are cheap, it is affordable to have a very large amount of storage at this level. Hard disks are at the very bottom of the storage hierarchy. Today, a single enterprise-class server can hold terabytes of data in the main memory. Dramatic drops in price accompany the drastic growth of the main memory capacity that you get on a single computer. NewĬomputer architectures have changed over the last few decades. Thus, you can execute them without disk I/O. Also to ensure the read options can anticipate that all relevant data resides permanently in the main memory. In order to process massive quantities of data in main memory and provide immediate results for both analysis and transaction, SAP HANA deploys the following activities: SAP HANA Database keeps data In MemoryĪlthough SAP HANA Database keeps data in memory, you still need non-volatile storage to ensure the write operations are durable.
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