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elasticsearch-metrics-reporter-java | Metrics reporter , which reports to elasticsearch | Analytics library

 by   elastic Java Version: Current License: Apache-2.0

 by   elastic Java Version: Current License: Apache-2.0

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kandi X-RAY | elasticsearch-metrics-reporter-java Summary

elasticsearch-metrics-reporter-java is a Java library typically used in Analytics applications. elasticsearch-metrics-reporter-java has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.
This is a reporter for the excellent Metrics library, similar to the Graphite or Ganglia reporters, except that it reports to an Elasticsearch server. In case, you are worried, that you need to include the 20MB elasticsearch dependency in your project, you do not need to be. As this reporter is using HTTP for putting data into elasticsearch, the only library needed is the awesome Jackson JSON library, more exactly the Jackson Databind library to easily serialize the metrics objects. If you want to see this in action, go to the samples/ directory and read the readme over there, to get up and running with a sample application using the Metrics library as well as a dashboard application to graph.
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kandi-support Support

  • elasticsearch-metrics-reporter-java has a low active ecosystem.
  • It has 230 star(s) with 107 fork(s). There are 292 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 18 open issues and 15 have been closed. On average issues are closed in 53 days. There are 7 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of elasticsearch-metrics-reporter-java is current.
This Library - Support
Best in #Analytics
Average in #Analytics
This Library - Support
Best in #Analytics
Average in #Analytics

quality kandi Quality

  • elasticsearch-metrics-reporter-java has 0 bugs and 0 code smells.
This Library - Quality
Best in #Analytics
Average in #Analytics
This Library - Quality
Best in #Analytics
Average in #Analytics

securitySecurity

  • elasticsearch-metrics-reporter-java has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • elasticsearch-metrics-reporter-java code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
This Library - Security
Best in #Analytics
Average in #Analytics
This Library - Security
Best in #Analytics
Average in #Analytics

license License

  • elasticsearch-metrics-reporter-java is licensed under the Apache-2.0 License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.
This Library - License
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This Library - License
Best in #Analytics
Average in #Analytics

buildReuse

  • elasticsearch-metrics-reporter-java releases are not available. You will need to build from source code and install.
  • Build file is available. You can build the component from source.
  • Installation instructions, examples and code snippets are available.
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Top functions reviewed by kandi - BETA

kandi has reviewed elasticsearch-metrics-reporter-java and discovered the below as its top functions. This is intended to give you an instant insight into elasticsearch-metrics-reporter-java implemented functionality, and help decide if they suit your requirements.

  • Report a batch of metrics .
    • main method for testing
      • Checks if an index template already exists .
        • Performs Elasticsearch .
          • Makes a histogram .
            • Returns a string representation of the given date in milliseconds .
              • Sends a notification for a given metric
                • Creates index and mapping if necessary .
                  • Add custom serializers .
                    • Opens a connection to the URL

                      Get all kandi verified functions for this library.

                      Get all kandi verified functions for this library.

                      elasticsearch-metrics-reporter-java Key Features

                      Metrics reporter, which reports to elasticsearch

                      Installation

                      copy iconCopydownload iconDownload
                      <dependency>
                        <groupId>org.elasticsearch</groupId>
                        <artifactId>metrics-elasticsearch-reporter</artifactId>
                        <version>2.2.0</version>
                      </dependency>
                      

                      Configuration

                      copy iconCopydownload iconDownload
                      final MetricRegistry registry = new MetricRegistry();
                      ElasticsearchReporter reporter = ElasticsearchReporter.forRegistry(registry)
                          .hosts("localhost:9200", "localhost:9201")
                          .build();
                      reporter.start(60, TimeUnit.SECONDS);
                      

                      Notifications with percolations

                      copy iconCopydownload iconDownload
                      ElasticsearchReporter reporter = ElasticsearchReporter.forRegistry(registry)
                          .percolationNotifier(new PagerNotifier())
                          .percolationFilter(MetricFilter.ALL)
                          .build();
                      reporter.start(60, TimeUnit.SECONDS);
                      

                      Counter

                      copy iconCopydownload iconDownload
                      {
                        "name": "usa-gov-heartbearts",
                        "@timestamp": "2013-07-20T09:29:58.000+0000",
                        "count": 18
                      }
                      

                      Timer

                      copy iconCopydownload iconDownload
                      {
                        "name" : "bulk-request-timer",
                        "@timestamp" : "2013-07-20T09:43:58.000+0000",
                        "count" : 114,
                        "max" : 109.681,
                        "mean" : 5.439666666666667,
                        "min" : 2.457,
                        "p50" : 4.3389999999999995,
                        "p75" : 5.0169999999999995,
                        "p95" : 8.37175,
                        "p98" : 9.6832,
                        "p99" : 94.68429999999942,
                        "p999" : 109.681,
                        "stddev" : 9.956913151098842,
                        "m15_rate" : 0.10779994503690074,
                        "m1_rate" : 0.07283351433589833,
                        "m5_rate" : 0.10101298115113727,
                        "mean_rate" : 0.08251056571678642,
                        "duration_units" : "milliseconds",
                        "rate_units" : "calls/second"
                      }
                      

                      Meter

                      copy iconCopydownload iconDownload
                      {
                        "name" : "usagov-incoming-requests",
                        "@timestamp" : "2013-07-20T09:29:58.000+0000",
                        "count" : 224,
                        "m1_rate" : 0.3236309568191993,
                        "m5_rate" : 0.45207208204948995,
                        "m15_rate" : 0.5014348927301423,
                        "mean_rate" : 0.4135529888278531,
                        "units" : "events/second"
                      }
                      

                      Histogram

                      copy iconCopydownload iconDownload
                      {
                        "name" : "my-histgram",
                        "@timestamp" : "2013-07-20T09:29:58.000+0000",
                        "count" : 114,
                        "max" : 109.681,
                        "mean" : 5.439666666666667,
                        "min" : 2.457,
                        "p50" : 4.3389999999999995,
                        "p75" : 5.0169999999999995,
                        "p95" : 8.37175,
                        "p98" : 9.6832,
                        "p99" : 94.68429999999942,
                        "p999" : 109.681,
                        "stddev" : 9.956913151098842,}
                      }
                      

                      Gauge

                      copy iconCopydownload iconDownload
                      {
                        "name" : "usagov-incoming-requests",
                        "@timestamp" : "2013-07-20T09:29:58.000+0000",
                        "value" : 123
                      }
                      

                      Community Discussions

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                      QUESTION

                      Lottery analysis for learning

                      Asked 2022-Mar-31 at 15:00

                      I'm trying to learn how to use the pandas library.

                      For the data source, I use the lottery combinations draws so far.

                      One of many tasks I'm trying to solve is to count the frequency of pairs of numbers in combinations.

                      I create a data frame from the list like this:

                      list = [
                          [13, 14, 28, 30, 31, 37, 39],
                          [7, 10, 12, 16, 21, 22, 33],
                          ...,
                          [1, 2, 7, 15, 25, 31, 33],
                          [3, 6, 18, 21, 31, 34, 39]
                      ]
                      
                      df = pd.DataFrame(list)
                      print(df.head())
                      

                      Output:

                      .   0   1   2   3   4   5   6
                      0   9  11  12  18  20  26  35
                      1  10  13  15  20  21  25  35
                      2   1   8  17  21  22  27  34
                      3  10  13  17  18  21  29  37
                      4   5   8  12  17  19  21  37
                      

                      For example, as a result I want to get the sum of how much time tuples of two or three numbers appear together in combinations:

                      Pair  : Found n time in all combinations
                      9,23  : 33
                      11,32 : 26
                      

                      Can you give me some directions or example how to solve this task, please?

                      ANSWER

                      Answered 2022-Mar-12 at 15:09

                      Here is a simple solution using just modules from the standard library:

                      from itertools import combinations
                      from collections import Counter
                      
                      draws = [
                          [13, 14, 28, 30, 31, 37, 39],
                          [7, 10, 12, 16, 21, 22, 33],
                          [1, 2, 7, 15, 25, 31, 33],
                          [3, 6, 18, 21, 31, 34, 39]
                      ]
                      
                      duos = Counter()
                      trios = Counter()
                      
                      for draw in draws:
                          duos.update(combinations(draw, 2))
                          trios.update(combinations(draw, 3))
                      
                      print('Top 5 duos')
                      for x in duos.most_common(5):
                          print(f'{x[0]}: {x[1]}')
                      
                      print()
                      
                      print('Top 5 trios')
                      for x in trios.most_common(5):
                          print(f'{x[0]}: {x[1]}')
                      

                      The code snippet above will result in the following output:

                      Top 5 duos
                      (31, 39): 2
                      (7, 33): 2
                      (13, 14): 1
                      (13, 28): 1
                      (13, 30): 1
                      
                      Top 5 trios
                      (13, 14, 28): 1
                      (13, 14, 30): 1
                      (13, 14, 31): 1
                      (13, 14, 37): 1
                      (13, 14, 39): 1
                      
                      

                      And here is a slightly more elegant version:

                      from itertools import combinations
                      from collections import Counter
                      
                      draws = [
                          [13, 14, 28, 30, 31, 37, 39],
                          [7, 10, 12, 16, 21, 22, 33],
                          [1, 2, 7, 15, 25, 31, 33],
                          [3, 6, 18, 21, 31, 34, 39]
                      ]
                      
                      counters = [Counter() for _ in range(3)]
                      
                      for n, counter in enumerate(counters, 2):
                          for draw in draws:
                              counter.update(combinations(draw, n))
                      
                          print(f'Top 10 combos of {n} numbers')
                      
                          for combo, count in counter.most_common(10):
                              print(' '.join((f'{_:2d}' for _ in combo)), count, sep=': ')
                      
                          print()
                      

                      Which will give us the following output:

                      Top 10 combos of 2 numbers
                      31 39: 2
                       7 33: 2
                      13 14: 1
                      13 28: 1
                      13 30: 1
                      13 31: 1
                      13 37: 1
                      13 39: 1
                      14 28: 1
                      14 30: 1
                      
                      Top 10 combos of 3 numbers
                      13 14 28: 1
                      13 14 30: 1
                      13 14 31: 1
                      13 14 37: 1
                      13 14 39: 1
                      13 28 30: 1
                      13 28 31: 1
                      13 28 37: 1
                      13 28 39: 1
                      13 30 31: 1
                      
                      Top 10 combos of 4 numbers
                      13 14 28 30: 1
                      13 14 28 31: 1
                      13 14 28 37: 1
                      13 14 28 39: 1
                      13 14 30 31: 1
                      13 14 30 37: 1
                      13 14 30 39: 1
                      13 14 31 37: 1
                      13 14 31 39: 1
                      13 14 37 39: 1
                      

                      Source https://stackoverflow.com/questions/71449837

                      Community Discussions, Code Snippets contain sources that include Stack Exchange Network

                      Vulnerabilities

                      No vulnerabilities reported

                      Install elasticsearch-metrics-reporter-java

                      You can simply add a dependency in your pom.xml (or whatever dependency resolution system you might have).

                      Support

                      For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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