elasticsearch query performance tuning

are very readable6. Use where to replace having (if possible)Optimize GROUP BY:Increase the efficiency of the group BY statement by filtering out unwanted records before group by. The following two queries return the same result but the second one is significantly faster. Copy the code code as follows: Low efficiency:SELECT JOB, AVG (SAL)From EMP GROUP job has job = ' president ' and AVG (SAL) >xxxEfficient:SELECT JOB, AVG (SAL)From EMPWHERE JOB = ' President 'OR job = ' MANAGER ' GROUP JOB hav

Oracle is a high-performance database software. The user can adjust the parameters to achieve the optimization of performance. Performance optimization is mainly divided into two parts: First, the database administrator through the adjustment of system parameters to achieve the goal of optimization; The second is that the developer achieves the adjustment by op

; set [global] Variable name = value;Permanently definedVim/etc/my.cnf[Mysqld]Variable name = value....: Wq#systemctl Restart MysqldMySQL architecture?Connection poolSQL interfaceAnalyzerOptimizerQuery cacheStorage EngineFile systemManagement toolsHow does the MySQL service process query requests?4 The SQL query command of the query database written by the progra

query time, resulting in slower efficiency. The workaround is to use the index for sorting. If the order required for the query is the same as the sort used by the index, because the indexes are sorted, and therefore the results are returned in sequential read by index, the using Filesort does not appear at this time.As for the difference between using index and using index condition, I refer to an article

When we are doing SQL optimization, we often encounter the need to sort a large number of datasets and then take the results from the pre-ordered collection, in which case, when we follow the usual thinking to write SQL, the system will read the filter to get all the collection, then sort, and then take out a very small number of results from the sorting results, the process, The scanning, filtering, sorting of large amounts of data consumes a large amount of system resources, and SQL

released, the data page will not be in the memory of the data cache, This causes the memory problem to be the bottleneck of the disk. PAGEIOLATCH_EX is write data, this is generally the disk write speed obviously keep up, and memory is not directly related. Here is the resource wait time for query pageiolatch_x: Select Wait_type, waiting_tasks_count, Wait_time_ms, Max_wait_time_ms, Signal_wait_time_ms from sys.dm_os_wait_stats wherelike' pageiolat

. The Block Nested-loop algorithm uses the result set of the driver table (which can be simply understood as the preceding table) as the circular underlying data, and then one article queries the data in that result set by using the data in the resulting dataset as a filter to the next table, and then merges the results. If there is a third participating join, then the join result set of the previous two tables is used as the base data for the join, once again querying the data by looping throug

When there are performance problems in our system, we often avoid investigating various types of lock wait, such as row lock wait, page lock wait, page IO Latch wait, and so on. To find out the possible abnormal waiting, for performance optimization to do a certain reference. The specific query statements are shared as follows,/***********************************

not in with not existsIn a subquery, the NOT IN clause performs an internal sort and merge, in either case, not in is the least effective because it performs a full table traversal of the table in the subquery, and in order to avoid using not, it can be written as an outer join (Outer Joins) or not EXISTSLow efficiencySELECT *FROM dbo. OrdersWHERE id_p>0 and Id_p not in (SELECT IdFROM dbo. Persons)EfficientSELECT *From OrdersWHERE id_p >0 and not EXISTS (SELECT IdFrom Persons WHERE persons.id =

) GTID2) in MySQL 5.6 gtid mode synchronous replication error cannot skip the workaround3) Improvement of Gtid replication in MySQL5.74) Gtid Replication traps5) Improvements to Gtid replication in MariaDB 10.1MySQL 5.6/5.7 Security recovery from library crashMariaDB 10.0/10.1 security recovery from vault crashSlave multi-threaded replication from librariesSlave supports multi-source replicationMySQL 5.7 Set synchronous replication filtering without restarting the MySQL service processThis artic

Tags: default int query full table scan condition index default policy wildcard1. Building an Index2. Avoid full table scanAvoid using is null, which is not NULL, so that writing discards the index of the field.If this is the case, try to set the default value when designing the tableCompare operators in! = Use less intLike wildcards try to put wildcards behind "qw%" and do not use fuzzy queries, which use the indexwhere L = R use less function operat

PHP tutorials and MySQL tutorial performance tuning notes The larger the tmp_table_size=200m tmp_table_size, the smaller the probability of being converted to a disk TMP table PHP Program page MySQL closed in time Set the MySQL timeout timeLow-priority-updates set query and update priority and tmp_table_size=200m; The greater the use of memory, the moreLow_

MONGODB1, MongoDB optimization: A, statement optimization may find a long execution time statement through the profile. Db.getProfiling.Level () to get the profile level Db.system.profile.find () to view the profile record. B, after finding the statement, through the explain to parse the statement, you can see whether the index is used, what index? Db.collection.find ({xx:xx}). Explain (); C, through the results of explain to optimize the query statem

, Microseconds_per_second ms_per_sec, pct_of_time pct from Opsg_delta_report where Microseconds_per_second > 0; Monitoring the usage of indexes: With In_plan_objects as(SELECT DISTINCT object_name from V$sql_plan WHERE object_owner = ' SCOTT ')SELECT table_name,Index_name,CaseWhen object_name was NULL then' NO 'ELSE' YES 'END as In_cached_planFrom User_indexesLeft OUTER JOIN in_plan_objectsOn (index_name = object_name);4. Identify the SQL statements that benefit from the binding variab

The first thing to note is that the content of this article is not how to tune SQL Server query performance (about which you can write a book), but how to leverage the set STATISTICS IO and set STATISTICS in SQL Server query performance tuning Time these two frequently ignor

Tags: database tuning database MySQL slow query performance optimization First, find slow query We talked about the definition of a slow query, which we create a large table for data preparation for slow queries. 2. Slow query

waste. Query Cache Fragmentation Rate = Qcache_free_blocks/qcache_total_blocks * 100% If the query cache fragmentation rate exceeds 20%, you can use flush query cache to defragment the cache. Or try reducing query_cache_min_res_unit if your queries are small data volumes. Query Cache utilization = (query_cache_s

The more CPU and IO resources a query requires, the slower the query speed. Therefore, another way to describe the query performance tuning task is, the query command should be rewritten in a way that uses less CPU and IO resource

From: http://www.itqun.net/content-detail/104196.html Set statistics profile on Set statistics Io on Set statistics time on The more CPU and IO resources a query requires, the slower the query speed. Therefore, another way to describe the query performance tuning