Using caches for stream readers:
When readers read a stream from beginning to end, they become easy to scale. This is simple strategy and works well for parallelizing computations. However, it introduces latency as streams can be quite long.
A cache served to provide the stream segments do that clients font have to go all the way to the store. It could employ a group of readers that could replenish the segments that are in most demand. There is always the option for clients to reach the store if the cache does not have what it needs. Generally s cache will bring in the segment on behalf of the client if it goes not have it.
The techniques for providing stream segments do not matter to the client and the cache can use any algorithm. The cache also provides the benefits of alleviating load from the stream store without any additional constraints. In fact the cache will also use the same stream reader as the client and with the only difference that there will be fewer stream readers on the stream store than before.
The cache essentially projects portions of the stream so that the entire stream does not have to scanned from begin to end repeatedly. This mode of operation is different from finding popular stream segments across stream readers.
The cache may use a queue to hold contiguous segments from a stream.
The choice of queue is extremely important for peak throughput. The use of a lock free data structure as opposed to an ArrayBlockingQueue can do away with lock contention. The queues work satisfactorily until they are full. Garbage free Async stream readers have the best response time.
The benefits here are similar to LogAppenders except that they are on write path whole these are in read path.
Asynchronous read together with lock free access and skip level access boost performance. The cache may encounter significant size for each segment and a writer that transfers a segment over the network may take time in the order of hundreds of milliseconds. Instead, having a continuous background import for adjustable window of steam segments tremendously improves the load on the stream store while responding to seek requests on segments
When readers read a stream from beginning to end, they become easy to scale. This is simple strategy and works well for parallelizing computations. However, it introduces latency as streams can be quite long.
A cache served to provide the stream segments do that clients font have to go all the way to the store. It could employ a group of readers that could replenish the segments that are in most demand. There is always the option for clients to reach the store if the cache does not have what it needs. Generally s cache will bring in the segment on behalf of the client if it goes not have it.
The techniques for providing stream segments do not matter to the client and the cache can use any algorithm. The cache also provides the benefits of alleviating load from the stream store without any additional constraints. In fact the cache will also use the same stream reader as the client and with the only difference that there will be fewer stream readers on the stream store than before.
The cache essentially projects portions of the stream so that the entire stream does not have to scanned from begin to end repeatedly. This mode of operation is different from finding popular stream segments across stream readers.
The cache may use a queue to hold contiguous segments from a stream.
The choice of queue is extremely important for peak throughput. The use of a lock free data structure as opposed to an ArrayBlockingQueue can do away with lock contention. The queues work satisfactorily until they are full. Garbage free Async stream readers have the best response time.
The benefits here are similar to LogAppenders except that they are on write path whole these are in read path.
Asynchronous read together with lock free access and skip level access boost performance. The cache may encounter significant size for each segment and a writer that transfers a segment over the network may take time in the order of hundreds of milliseconds. Instead, having a continuous background import for adjustable window of steam segments tremendously improves the load on the stream store while responding to seek requests on segments
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