tablet metrics

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Go LoadRunner 17 metrics for monitoring Linux

Ethernet packets.10, outgoing packets rate:outgoing Ethernet packets per secondThe number of outgoing Ethernet packets per second.11. Page-in Rate:number of pages read to physical memory, per secondThe indicator indicates the number of pages exchanged to physical memory per second.12. Page-out Rate:number of pages written to pagefile (s) and removed from physical memory, per secondRepresents the number of pages per second that are removed from physical memory or written to the page.13. Paging R

MySQL Performance bottleneck analysis, performance indicators, metrics collection methods and performance analysis tuning tools

Label:This paper mainly explains MySQL performance bottleneck analysis, performance indicators, performance index information collection tools and methods, analysis of the use of tuning tools.The article has not been completed, the following is an outline.Performance bottlenecks:SlowPerformance Index:Frequency of VisitsNumber of concurrent connectionsCache Hit RatioIndex useSlow log opening and analysisQuery LogIndicator Information collection:Dstat--mysql5-io--mysql5-cmds--mysql5-keys "See refe

Machine Learning Algorithms Excellence: Metrics

Evaluation algorithm Excellent program, commonly used a series of indicators to measure, mainly including: Precision,recall,f-1 score, why design these values? Can't I use precision alone?1, what is precision?Precison, accuracy, mainly indicates how much of the detected alert is the correct judgment (True POSITIVE,TP).In practice, due to the different proportions of normal and abnormal data in the sample, accuracy can not reflect the real algorithm performance, for example:Cancer detection: It i

Sort comparison Metrics

Indicators that measure the difference of two orders1. Fitness\[F = \frac{1}{z} \sum_j \frac{w_j}{\alpha (|p_i-q_j|+1) + (1-\alpha) p_i} \]which $p _j$ The position of the result of section $j$ in the sorted order $q _j$ The position of the $j$ result of the sorted order in the standard sort $w _j$ the weights on position $j$ in the standard sort $Z $ normalization factor 2. Kendall tau distance (wikipedia)\[k = \frac{2}{n (N-1)} \sum_{i=1}^{n-1} \sum_{j\[k (i,j) = \begin{cases}

Python implements Linux KVM system monitoring metrics, written many years ago to help colleagues, quickly learn Python technology

#!/usr/bin/envpython#-*-coding:utf8-*-"" "@Author :villiamsheng@group: LinuxGroup@Date:2011-07-18@Funtion: Updatekvmhoststatus... get_nic:getaweeknetwork flow1, getsevendaysbeforeflow,getmaximumvalue! 2,GetSevendaysbefore flow,getaveragevalue! "" "Importos,sys,libvirt,socket,shutil,refromstatvfs importf_blocks,f_bavail,f_bsizeclasskvm_os_status (object): def __init__ (self): NBSP;NBsp;self.vmm={} Try:self.conn=libvirt.open (None) exceptlibvirt.libvirtError,e: printedefget_ Mem (self):try: f=open

The stress test measures three CPU metrics: CPU utilization, Load average, and context Switch Rate

TPS in the formula to get the number of transitions that each thing causes. Therefore, to reduce the CSR, you must work on the switch caused by each TPS, only n this value down, the CSR can be reduced, ideally n=0, but in any case, if n >= 4, you should check. In addition to the online csr Additional Information: These three metrics can be monitored in loadrunner, and in Linux, you can also use Vmstat to view R (Load arerage), in (Interrupt) and

Some commonly seen metrics in SQL Server and methods for clearing the cache _mssql

How to view disk I/O operation information The SET STATISTICS IO on command is a message that enables SQL Server to display information about the amount of disk activity generated by Transact-SQL statements. We can be very useful when analyzing index performance. With this property enabled, after executing the SQL statement, we receive information similar to the following, which helps us analyze SQL performance: (3999 row (s) affected) Table ' Chargecl '. Scan count 1, logical read 9,547 times

Performance metrics for classifiers

I. Assessment METHODOLOGY 1. Leave the method The set up method directly divides the dataset D into two mutually exclusive collections, one of which is used as the training set S and the other as the test set T, and the T is used to evaluate the test error as an estimate of the generalization error when the model is trained at S. 2. Cross-validation method "Cross-validation" first divides the dataset D into K-sized mutually exclusive subsets, each of which maintains the consistency of the data d

MongoDB finds the minimum or maximum value based on the metrics in the subkey

student's performance, use the following statement: db.students.aggregate([{$project: {minScore: {$min: "$scores.score"}}}]) The statement inside minScore is equal to an alias and can be used for other. The results are as follows: { "_id" : 1, "minScore" : 34.85718117893772 } { "_id" : 3, "minScore" : 1.694720653897219 } { "_id" : 2, "minScore" : 6.301851677835235 } { "_id" : 4, "minScore" : 19.21886443577987 } { "_id" : 5, "minScore" : 10.53058536508186 } { "_id" : 7, "minScore" : 42.487806669

Monitor common metrics for SQL Server with Windows Performance Monitor

, occasionally do not have to worry about, if a long time, then you have to start to consider solving the disk IO performance issues.6.Processor:% Processor timeThis is an indicator for monitoring CPU conditions (similar to disk Time). This is a key parameter for observing CPU utilization. If the value of the processor Time counter continues to exceed 80%, there is a bottleneck on the CPU. If it only happens occasionally, it may indicate that there is a particular CPU-consuming query at this poi

How query optimization uses SQL statements to view performance metrics for queries

time. However, this number will be different each time the query is run, except that the range of changes does not vary greatly over time. The total time is the amount of time that is required to execute the query (no time to block or read data), and because the load on the server is constantly changing, the range of this data can sometimes be quite large. In general, the performance of a query statement can be compared in several parameters in a quantitative way: 1, CPU time. Compare the CPU r

MySQL Monitoring metrics

InnoDB table to monitor the remaining space of the InnoDB table.21.QPS Query volume per secondQPS = Questions (or Queries)/secondsMySQL > Show/* global * * status like ' Question ';22.TPS (transaction volume per second)TPS = (com_commit + com_rollback)/secondsMySQL > Show status like ' Com_commit ';MySQL > Show status like ' Com_rollback ';23.key Buffer hit RatioKey_buffer_read_hits = (1-key_reads/key_read_requests) * 100%Key_buffer_write_hits = (1-key_writes/key_write_requests) * 100%Mysql> Sh

Linux System performance metrics monitoring

/s rkb/s wkb/s avgrq-sz avgqu-sz await r_await w_await SVCTM%utilVDA 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00iostat-x VDA 1 2 command meaning: Every 1 seconds print the VDA this disk usage information, print two times altogether. %util indicates CPU busy, higher and busierUniversal Command-SAR(System Activity Report) is one of the most comprehensive systems performance analysis tools available on Linux and can be used to report system activity in many ways.Performance mon

Jmeter:windows server and Linux server performance metrics collection

1.0 Download serveragent. zipDownloadhttps://jmeter-plugins.org/wiki/PerfMonAgent/in the Serveragent.zip, store it in the JMeter directory and unzip it.1.1 Jmeter-winBefore testing the win performance, start the bat file and start the SH file before testing Linux.Note:① data must have a writable file, otherwise it will error, unable to execute the test plan. (The fact that my home notebook error, the company does not error)The length of the ② thread group is set longer, otherwise the time is too

Windows Server performance monitoring tools, methods, and key metrics

indicator that can display system-wide delay type errors. It is the sum of memory\\pages input/sec and memory\\pages output/sec . is calculated using the number of pages, so that it can be compared with other page counts, such as memory\\page faults/sec , without having to do the conversion , which includes the file system cache to satisfy the error ( typically requested by the application The page is retrieved in a non-cached mapped memory file. Recommended indicatorsThis value should not exc

Linux CPU metrics

Linux CPU metrics Linux provides a wealth of commands to monitor CPU-related data, such as top and vmstat. Top is a dynamic display process, that is, you can press the key to continuously refresh the current status. If you execute this command on the foreground, it will exclusively occupy the foreground until the user terminates the program. More accurately, the top command provides real-time monitoring of the status of the system processor, it displa

[Method] outputs the running metrics of workflow to target, and workflowtarget

[Method] outputs the running metrics of workflow to target, and workflowtarget Take the output workflow start time as an example: First, create the workflow-level variable $ test (datetype: date/time) in workflow) Next, double-click the link after Start and assign starttime to the newly defined wk variable $ test. Return to the Designer and add the mapping-level variable $ test (datetype: date/time) to the mapping) Return to Workflow Manage

Code quality metrics (resource standard management)

RSM is a good staticCodeQuality Check tool, provide code line statistics, complexity statistics and other functions, see: http://msquaredtechnologies.com/m2rsm/docs/index.htm RSM supports the languageSyntax of ansi c, ansi c ++, C # and Java. RSM creates HTML reportsFor visual metrics that interacts with source code hyperlinks and CSV or commaSeparated value format for direct input to MS Excel or other spreadsheets. Feature: Number of

Zabbix Monitoring HDD metrics, TCP connection status

} ';; NBSP;NBSP;NBSP;NBSP;NBSP;AVGRQ-SZ) /usr/bin/iostat-dx|grep $device |awk ' {print$8} ';; NBSP;NBSP;NBSP;NBSP;NBSP;AVGQU-SZ) /usr/bin/iostat-dx|grep $device |awk ' {print$9} ';; await) /usr/bin/iostat-dx|grep $device |awk ' {PRINTNBSP;$10} ';; NBSP;NBSP;NBSP;NBSP;NBSP;NBSP;NBSP;NBSP;SVCTM) /usr/bin/iostat-dx|grep $device |awk ' {print$11} ';; util) /usr/bin/iostat-dx|grep $device |awk ' {print$12} ';; EsacModify the Zabbix_agentd.conf file[Email protected] etc]$ Tail-2 zabbix_agentd.con

Collaborative filtering of user similarity metrics

, 2) #Now compute Denominatordenominator = sqrt (Sum_x2-pow (sum_x, 2)/N) * sqrt (Sum_y2-pow (sum_y, 2)/N)ifDenominator = =0:return0Else: return(Sum_xy-(sum_x * sum_y)/n)/denominatorSelection of Similarity:The Pearson correlation coefficient is used when different users have different evaluation criteria for various products.When the data is dense and the value of the attribute is important, use Euclidean or Manhattan distances;When the data is sparse, there are many 0 values, consider

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