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Index[SYMBOL] [A] [B] [C] [D] [E] [F] [G] [H] [I] [J] [K] [L] [M] [N] [O] [P] [Q] [R] [S] [T] [U] [V] [W] R-tree indexes RAID (redundant array of independent disks) 2nd 3rd disk drives implementing 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th 12th hardware-based levels RAID 0 (disk striping) 2nd RAID 0 (mirroring/duplexing) 2nd RAID 0+1 2nd MySQL software-based operating system software-based raw disk partitions benefits contiguous disk space (InnoDB) lower overhead (InnoDB) implementing (InnoDB) 2nd 3rd READ COMMITTED isolation level 2nd READ locks tables 2nd READ UNCOMMITTED isolation level 2nd 3rd 4th recording test results in performance analysis 2nd 3rd 4th recurrent events query caches 2nd 3rd Red Hat Linux System Monitor ref column EXPLAIN command (optimizer) output 2nd relay logs slave servers management of 2nd reloading data from data exports acceleration of 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th concurrency management 2nd 3rd error handling 2nd InnoDB engine recommendations 2nd INSERT DELAYED operation multirow INSERT operation 2nd MyISAM engine recommendations 2nd network performance parameters 2nd SELECT, INTO OUTFILE statement 2nd table locking 2nd REPEATABLE READ isolation level 2nd replicas data distribution node storage replicated slave servers query usage replicating databases performance analysis 2nd Replication distributed computing technology product replication performance issues master servers, monitoring 2nd 3rd 4th 5th 6th master servers, tuning practices master servers, when to log 2nd network considerations 2nd 3rd 4th 5th 6th 7th slave servers, configurations slave servers, data criteria 2nd slave servers, monitoring 2nd 3rd slave servers, overhead reduction 2nd slave servers, relay logs 2nd slave servers, resource management 2nd 3rd slave servers, shared workloads 2nd slave servers, temporary file storage queries processing work, off-loading 2nd servers master selection 2nd strategies design of 2nd 3rd 4th 5th 6th usage criteria 2nd versus clustering 2nd 3rd replication strategy transaction bottlenecks High-Hat Airways case study resolving application failures High-Hat Airways scenario 2nd 3rd 4th 5th 6th large-sale data importation problems High-Hat Airways 2nd 3rd 4th server clustering problems High-Hat Airways 2nd 3rd 4th 5th server outages High-Hat Airways scenario 2nd 3rd 4th 5th 6th stored procedure problems High-Hat Airways 2nd 3rd transaction failures High-Hat Airways scenario 2nd 3rd 4th 5th 6th resource consumption transaction length resource restriction strategy transaction bottlenecks High-Hat Airways case study results (testing) recording 2nd 3rd 4th resultsets queries DISTINCT statement 2nd estimating 2nd 3rd 4th GROUP BY statement 2nd limiting 2nd 3rd 4th retrieving data exports table subsets 2nd returned columns reducing for query performance 2nd returned rows reducing for query performance 2nd rollback segments transaction length rollbacks transaction length rollup strategy transaction bottlenecks High-Hat Airways case study row locks rowid values clustered indexes (InnoDB) 2nd rows locking scope (InnoDB) 2nd tables data handling (HANDLER statement) 2nd 3rd 4th specifying 2nd 3rd rows column EXPLAIN command (optimizer) output 2nd rules constraints benefits 2nd DEFAULT 2nd 3rd ENUM 2nd 3rd FOREIGN KEY 2nd 3rd 4th 5th 6th function of NOT NULL 2nd 3rd PRIMARY KEY 2nd 3rd SET 2nd 3rd 4th UNIQUE 2nd |
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