文本分析教案課程anti cache

1、The cache mechanism in H-Storeassumption: data wont fit in memory disk-resident data, main memory buffer pool for execution concurrency is a must transaction serialization and locksDBMS buffer pooldistributed cachein-memory DBMSmust still maintain buffer pool lock/latch data maintain ARIES-style rec

2、overy logsquestion: What is the overhead of all these things?fast and scalable, butkey-value interfacenot ACID (AI, not CD)H-Store Architecture partitioned, shared-nothing single-threaded main memory execution no need for locks and latcheslightweight recovery snapshots + command logbig: disk-oriente

3、dfast: memory-orientedbig and fast: anti-cachingasynchronous disk fetches dont blockmaintain ordering of evicted data accesses ensures transactional consistencysingle copy of data consistency is freeefficient memory use, no swizzlingmemory is primary storage, cold data is evicted to disk-based anti-

4、cachereading data from the anti-cache is done in 3 phases avoids blocking, ensures consistencyBlock Table This is a hash table that maintains the blocks of tuples that have been evicted from the DBMSs main memory storage.Evicted Table The Evicted Table keeps track of the tuples that have been writte

5、n out to blocks on disk. DBMS updates any indexes containing evicted tuples to reference the Evicted Table.LRU Chain: Lastly, H-Store also maintains an in-memory list of all the tuples for each table in LRU order.Evict 1. data anti-cache threshold 2. dynamically construct anticache blocks of coldest

6、 tuples 3. asynchronously write to diskpre-pass 1. a transaction enters pre-pass when evicted data is accessed 2. continues execution, creating list of evicted blocks 3. abort, queue blocks to be fetchedFetch 1. data is fetched asynchronously from disk and avoids blocking 2. moved into merge bufferM

7、erge 1. data is moved from in-memory merge buffer to in-memory table. Block-merging or Tuples-merging 2. previously aborted transaction is restarted 3. transaction executes normallydone online, more responsive to changes in workloadgoal is low CPU and memory overheadapproximate ordering is OKmaintain LRU chain embedded in tuple headersper-partitiontransactions that update LRU chain are sampled randomly configurable sample ratefine-grained evictionblocks constructed dynamicallyasynchronous batched fetchespossible because of transactionsdata exists in exactly one location caching archi