kafka metrics

70% 23.33% 5% 0.83% 0.83% CPU consumption Interval (%) 0.00~11.40 11.50~22.80 22.90~34.20 34.30~45.60 45.70~57.00 Number 120 0 0 0 0 Percentage 100% 0% 0% 0% 0% Memory consumption Interval (MB) 0.00~18.13 18.14~36.26 36.27~54.39 54.40~72.52 72.53~9

3014885 2127 139857 2117 3014885 2127 0 0 0 0 139857 2117 0 0 0 0where 6th and 8 are listed as Rx_bytes (receive data) and tx_bytes (transmit data) contain statistics on all network traffic such as TCP,UDP.Remarks: Script page http://www.cnblogs.com/penghong2014/p/4530875.html4. PowerMany features of Android are compared to power consumption (such as screen, Gps,sensor sensor, wake-up mechanism, CPU, Internet usage, etc.)1) Anti-screen standby the most power-saving2) WiFi than cellular data, in

Send monitoring metrics to the internal mailbox in LinuxDatabase health monitoring is a very important task. An important indicator/KPI monitoring result has a dedicated collection, monitoring, and alarm system for relevant tasks.Some indicators that are not very important or are still in the design and debugging phase, I just want to send them to my own mailbox. This article describes the process of configuring mail to send monitoring data on the ser

for memory use, so as not to cause frequent GC (garbage collection mechanism) impact performance and large object application memory overflow; On the other hand, we need to release memory in time to avoid a memory leak.ElectricityMobile devices have very limited battery power relative to the PC, which is especially important to maintain long-lasting endurance. In addition, many features of Android are more power consumption (such as screen, Gps,sensor sensor, wake-up mechanism, CPU, network, et

) Jaccard distanceThe concept opposite to the Jaccard similarity coefficient is the jaccard distance (jaccard distance). Jaccard distances can be expressed in the following formula:The Jaccard distance is used to measure the sensitivity of two sets by the proportion of the elements in each of the two sets.(3) Application of Jaccard similarity coefficient and Jaccard distanceThe Jaccard similarity coefficient can be used to measure the similarity of samples.Sample A and sample B are two n-dimensi

. The memory resources of the mobile device are very limited, and the private memory allocated for each app process is limited. On the one hand, we should reasonably apply for memory use, so as not to cause frequent GC (garbage collection mechanism) impact performance and large object application memory overflow; On the other hand, we need to release memory in time to avoid a memory leak.ElectricityMobile devices have very limited battery power relative to the PC, which is especially important t

Content is the most valuable part of a website. The only purpose of a user's access to your website is to obtain valuable content, rich content, and accurate content, the constantly updated content is three elements of a successful website. Of the 101 metrics of the perfect website, 23 are about content. We put the content first. In fact, you should focus 80% on the content, the 23 content indicators are: Rich Content It is hard to imagine the disapp

after.Summary:This small series introduces the relationship between the indicator and user behavior, as well as the calculation methods and advantages and disadvantages of each indicator. In the analysis of the site should be integrated use, in order to make the correct suggestions for improvement measures. For example, if a product is not focused, but the conversion rate is high, we should analyze how, and another product is very high, but the conversion rate is very low, we should analyze how

tcpdump to grab the packet, when the problem is reproduced (such as the log display or a state appears), you can end the capture, and the tcpdump itself with-c/-w parameters, you can limit the size of the crawl packet storage file, When this limit is reached, the saved packet data is automatically rotate, so the total number of packets is still controllable. After that the packet took off the line, with Wireshark want to see how to see, not happy! Tcpdump Although there is no GUI interface, but

/etc/mail.rc# for Linux and BSD, this should is set.Set BsdcompatSet from=[sender email address]Set SMTP=[SMTP server address]Set smtp-auth-user=[mailbox user name]Set smtp-auth-password=[Email password]Set Smtp-auth=loginManual test to send mail:[Email protected] etc]# echo Hello World |mail-s "test" [email protected][email protected] etc]# python dbcheck.py >dbcheck.txt;cat dbcheck.txt|mail-s dbcheck [email protected][email protected] etc]# python dbcheck.py >dbcheck.txt;mail-s dbcheck [email

higher the speedup, the more obvious the optimization effect. The Amdahl law gives the relationship between speedup and system parallelism and number of processors. Assuming that the speedup ratio is speedup, the program that must be serialized within the system is the F,CPU processor number n, which is:speedup≤1/(f+ (1-f)/n) Example: under a dual-core processor, a program execution step consists of 5 steps, of which 3 steps must be serial, so its serialization weight is f=3/5=0.6,n=2. Accordin

, the Markov distance between two points is independent of the unit of measurement of the original data, and the Markov distance between the normalized data and the central data (that is, the difference between the original data and the mean) is the same as that between two points. The Markov distance can also exclude the interference of correlations between variables. Cons: Its disadvantage is that it exaggerates the effects of small variables that change.Reference:Http://www.cnblogs.com/daniel

"Introduction" To some extent, E-commerce can be said to be the meaning of web analytics. This article explores one of the most common metrics for e-commerce sites: Abandonment Rate. Direct E-commerce analysis is less involved in this blog area, because I have been "immature" that E-commerce site analysis and our usual site analysis is not fundamentally different. After all, even if it is not an e-commerce site, it still has one (or more) can be quan

global statuslike ' open_files '; Mysql> mysql-e "show global statuslike ' open_tables '; (14) Slow query To turn on slow queries: Edit the/etc/my.cnf and add it in the [Mysqld] field: Slow_query_log= 1 # Turn on slow query Slow_query_log_file=/data/mysql/slow.log # Slow Query log path Long_query_time= 1 # Length of slow query To view the number of slow queries: Executive Mysqladminstatus (15) Full-time Records View full-day log: Show global variables like ' general_log '; Open full-day log:

parameterization.Sqlserver:sqlstatistics/failed auto-params/secNumber of failed automatic parameterization attempts per second. the value should be very small. Note that in later versions of SQL Server, automatic parameterization is also known as simple parameterization.Sqlserver:sqlStatistics/batch requests/secNumber of Transact- SQL command batches received per second. This statistic is affected by all constraints, such as I/O, number of users, cache size, complexity of the request, and so on

Tags: style blog http io color SP data div onOne, SET STATISTICS IO (about the amount of disk activity generated by the TSQL statement query) Scan Count: The number of times a table is accessed in a query;logical reads: The number of pages of data read from the data buffer;physical reads: The number of pages of data read from the physical disk to buffer;Read -ahead: The number of pages of data read from the physical disk to buffer according to the execution plan;--Displays information about

yarn-cluster --class Iteblog. Kafkatest 　　　　--jars lib/spark-streaming-kafka_2.10-1.3.0. Jar, Lib/spark-streaming_2.10-1.3.0. Jar, Lib/kafka_2.10-0.8.1.1.jar,lib/zkclient-0.3. Jar, Lib/metrics-core-2.2.0.jar./ Iteblog-1.0-snapshot.jarThe following is a complete example:Object Kafkawordcount {def main (args:array[string]) {if(Args.length ) {System.err.println ("Usage:kafkawordcount ) System.exit (1)} streamingexamples.setstreamingloglevels () Val Ar

户平均请求等待时间Time per request:14.972[MS] (mean, across all concurrent requests)#服务器平均请求处理时间Transfer Rate:20.71[kbytes/sec] Received#服务器的数据传输速度 (The data is the server egress bandwidth in the extreme case)Connection Times (MS)minMEAN[+/-SD]Median MaxConnect: + $ 4.8 $ -Processing: A $ 5.0 $ -Waiting: + $ 4.9 $ -Total:Bayi the 9.7 the thePercentage of theRequests servedwithin aCertain Time(MS) -% the #50% of requests completed within 92

PV (Page view) pageviewsViews, or clicks, when visitors visit the site, each time a webpage is opened, it is a PV.UV (unique Visitor) Independent visitorsVisitors to the site within a day of the visit, that is, a UV. Visitors are also credited with multiple visits during the day as a single UV.IpA different IP address in a day to access the site, record the number of different IP. The same IP is one time.Access depthThe depth of the website visit is the number of pages that visitors browse throu

MemoryCpuFlowElectricityStart speedSliding speedInterface switching speedNetwork speed for interacting with the serverExpected standard designation principle: 1) Analysis of competitor's products, all indicator keys are stronger than competing items2) Expected performance data from the product manager3) Meet industry standardsTest methods and tools:1: Memory, test with ADB shell script, view log data. adb shell dump Meminfo2:CPU: Test with adb shell script, view log data, adb shell top3: Traffic