Layman: HANA Memory Management
Imagine your computer. It has RAM (the fast memory) and a hard drive (where data is stored for the long-term).
1. RAM vs. Disk Storage:
RAM (Main Memory): This is like your brain's short-term memory. It's super fast but limited in size. SAP HANA stores data here for quick access and processing.
Disk Storage: This is like your brain's long-term memory or a bookshelf. It's slower to access, but you can store a lot more data. SAP HANA saves data here as a backup and for long-term storage.
2. Loading and Unloading Data:
Loading: When you need to think about something, you recall it from long-term memory to short-term memory. Similarly, SAP HANA loads data from Disk to RAM when it's needed.
Unloading: If your short-term memory gets full, you might forget something to make room for new information. In the same way, if HANA's RAM gets full, it will unload (remove) some data from RAM. The data still exists on the disk, so it's not lost.
3. Allocation and Deallocation:
Allocation: Think of it like opening a new book and reserving a spot on your desk for it. HANA reserves space in RAM for data it needs or expects to use.
Deallocation: When you're done with the book, you put it back on the shelf. Similarly, when HANA is done with certain data in RAM, it releases (deallocates) that space so other data can use it.
4. Garbage Collection:
Imagine you've done some arts and crafts, and there are scraps left on your table. Over time, you'll want to clean these up to make space. In HANA, "garbage collection" is the process of cleaning up memory areas that are no longer needed.
5. Compression:
Think of this as a space-saving technique. Imagine if you could press a big fluffy pillow into a small cube to save space in your cupboard. HANA does something similar with data – it "compresses" it so it uses less RAM.
6. Persistence Layer:
It's like a safety net. If your computer suddenly shuts down, everything in RAM might be lost. But, SAP HANA has a "persistence layer" that regularly saves RAM data to disk. So, even if something goes wrong, you don't lose all your data.
In short, SAP HANA Memory Management is all about efficiently using the fast memory (RAM) for performance, while also ensuring data is safely stored and can be retrieved when needed.
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Some more HANA Memory Termilogy from Layman's prespective:
In-Memory Computing: SAP HANA is fundamentally an in-memory database. This means that it stores the primary working set of data in the computer's main memory (RAM) rather than on traditional disk storage. This allows for much faster data access and processing times.
Persistence Layer: This is like a backup system for the data in RAM. While HANA is an in-memory database, it still uses disk storage to ensure that data isn't lost in case of a failure. The persistence layer regularly saves the data and logs from memory to disk.
Row Store vs. Column Store: HANA can store data in rows or columns.
Row Store: Traditional way of storing data, where each record (or row) is stored sequentially.
Column Store: HANA's default, where data is stored column by column. This allows for better compression and faster analytics.
Compression: To save space in memory, HANA compresses data, especially in the column store. This means that large amounts of data take up less space in RAM.
Allocation: The process of reserving space in RAM for data or processes. It's like setting aside a portion of memory for a specific task.
Deallocation: The opposite of allocation. It's the process of freeing up memory space that was previously reserved when it's no longer needed.
Garbage Collection: Over time, as data changes or is deleted, there may be chunks of memory that are no longer used. Garbage collection is the process of identifying and freeing up this "waste" memory.
Delta Storage: In HANA, when data changes, the changes are initially stored in a separate area called delta storage. After a certain point, these changes are merged back into the main storage (called the "main store").
Loading and Unloading:
Loading: Fetching data from disk storage and placing it into RAM for quick access.
Unloading: If memory is full or some data hasn't been accessed for a while, HANA might move it out of RAM and back to disk storage.
Resident Set Size (RSS): This refers to the amount of memory held in RAM for a particular process. In the context of HANA, it would refer to the memory used by the HANA processes.
Global Allocation Limit (GAL): This is a set limit on how much memory HANA can allocate. It's a safeguard to ensure that HANA doesn't use up all the system's memory.
Out of Memory (OOM) Situation: This occurs when HANA needs more memory than is available. In such cases, HANA might trigger garbage collection or unload data. If it still can't free up enough memory, it might lead to system issues or crashes.
Memory Pool: Grouped memory areas used for specific purposes. For example, a specific pool might be reserved for certain operations or data types.
This is a basic overview of the terms associated with SAP HANA Memory Management. Each of these topics can be delved into more deeply for a more comprehensive understanding, but this should give a foundational grasp of the concepts.
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