By Baron Schwartz, Peter Zaitsev, Vadim Tkachenko
How are you going to carry out MySQL’s complete strength? With High functionality MySQL, you’ll examine complex thoughts for every little thing from designing schemas, indexes, and queries to tuning your MySQL server, working method, and to their fullest power. This advisor additionally teaches you secure and sensible how one can scale purposes via replication, load balancing, excessive availability, and failover.
Updated to mirror contemporary advances in MySQL and InnoDB functionality, beneficial properties, and instruments, this 3rd variation not just deals particular examples of the way MySQL works, it additionally teaches you why the program works because it does, with illustrative tales and case experiences that show MySQL’s rules in motion. With this booklet, you’ll research how to think in MySQL.
• study the results of latest beneficial properties in MySQL 5.5, together with kept methods, partitioned databases, triggers, and views
• enforce advancements in replication, excessive availability, and clustering
• in achieving excessive functionality while operating MySQL within the cloud
• Optimize complex querying beneficial properties, comparable to full-text searches
• benefit from glossy multi-core CPUs and solid-state disks
• discover backup and restoration strategies—including new instruments for warm on-line backups
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Additional info for High Performance MySQL: Optimization, Backups, and Replication (3rd Edition)
E. a few important ﬂows transfer a significant number of packets. From the above observations, we see that a large number of ﬂows in the Internet have only a single packet. These ﬂows get entries into the digest cache, but will never be accessed again. Presence of a large number of such ﬂows has a detrimental eﬀect on the performance of the digest cache as they tend to evict the digests of few ﬂows that contain a large number of packets. 2 1 10 100 1000 Flow length 10000 100000 (b) NCAR trace 1e+06 0 1 10 100 1000 Flow length 10000 100000 (c) SDA trace Fig.
1. The memory size required to realize such a cache with suﬃciently high hit rate could be large due to the large size of the entries. A recent proposal has been to use a smaller digest of the 5-tuple instead of the actual values in the ﬁelds . 1 Operation of a Digest Cache We now describe the operation of the digest cache which was presented by Chang et al. . In case of packet classiﬁcation, a digest cache works by using a hashing algorithm on the 104-bit 5 tuple to generate a 32-bit hash 1 .
32-bits from the MD5 hash of the ﬂow identiﬁer is used to obtain the digest. The cache sizes for diﬀerent conﬁgurations are shown in Table 1. (a) 512 entries, 4-way set (b) 1024 entries, 4-way set (c) 2048 entries, 4-way set Fig. 5. Normalized misses for a 4-way associative digest cache For the traces listed in Table 2. Fig. 5 shows the percentage of misses with SP and PRED replacement policies. The misses are normalized wrt. misses incurred with LRU replacement for 4-way set associative caches.