Today we continue discussing the best practice from storage engineering :
255) Update in place and historical queries real-time challenges. If the values of the updates are maintained with their chronological order, then the queries may simply respond with the values of recent past. Such a collection of queries with answers from the same point of time are compatible
256) Catalogs maintained in storage products tend to get large. A sufficient allocation may need to be estimated. This is not always easy to do with the back of the envelope calculation but allowing the catalog to grow elastically is a good design practice
257) Memory allocation is a very common practice in data path. The correct management of memory is required for programming as well as performance. A context based memory allocator is often used. It involves the following steps: A context is created with a given name or type. A chunk is allocated within a context The chunk of memory is deleted within a context after use. The context is then deleted and then reset. Alternatively, some systems are implemented in languages with universal runtime and garbage collection to utilize the built-in collection and finalization.
258) Memory contexts provide more control than garbage collectors. Developers can provide both spatial and temporal locality of deallocation. Garbage collectors work on all of a program’s memory but some languages offer ways to tune up the garbage collection for specific servers.
259) Overheads may be reduced by not requiring as many calls to kernel as there are user based requests. It is often better to consolidate them in bulk mode so that majority of the calls return in a shallow manner.
260) Administrators are often tasked with provisioning sufficient memory on all compute resources associated with the storage product. With t-shirt sized commodity virtual machines, this is only partially addressed because that only specifies the physical memory. Virtual memory and it a usage must be made easier to query so that corrective measures may be taken.
255) Update in place and historical queries real-time challenges. If the values of the updates are maintained with their chronological order, then the queries may simply respond with the values of recent past. Such a collection of queries with answers from the same point of time are compatible
256) Catalogs maintained in storage products tend to get large. A sufficient allocation may need to be estimated. This is not always easy to do with the back of the envelope calculation but allowing the catalog to grow elastically is a good design practice
257) Memory allocation is a very common practice in data path. The correct management of memory is required for programming as well as performance. A context based memory allocator is often used. It involves the following steps: A context is created with a given name or type. A chunk is allocated within a context The chunk of memory is deleted within a context after use. The context is then deleted and then reset. Alternatively, some systems are implemented in languages with universal runtime and garbage collection to utilize the built-in collection and finalization.
258) Memory contexts provide more control than garbage collectors. Developers can provide both spatial and temporal locality of deallocation. Garbage collectors work on all of a program’s memory but some languages offer ways to tune up the garbage collection for specific servers.
259) Overheads may be reduced by not requiring as many calls to kernel as there are user based requests. It is often better to consolidate them in bulk mode so that majority of the calls return in a shallow manner.
260) Administrators are often tasked with provisioning sufficient memory on all compute resources associated with the storage product. With t-shirt sized commodity virtual machines, this is only partially addressed because that only specifies the physical memory. Virtual memory and it a usage must be made easier to query so that corrective measures may be taken.
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