refinery | aware tail-based sampling proxy | Analytics library

 by   honeycombio Go Version: v1.21.0 License: Apache-2.0

kandi X-RAY | refinery Summary

kandi X-RAY | refinery Summary

refinery is a Go library typically used in Analytics applications. refinery has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Refinery is a trace-aware sampling proxy. It collects spans emitted by your application, gathers them into traces, and examines them as a whole. This enables Refinery to make an intelligent sampling decision (whether to keep or discard) based on the entire trace.
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            kandi-support Support

              refinery has a low active ecosystem.
              It has 193 star(s) with 72 fork(s). There are 42 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 48 open issues and 116 have been closed. On average issues are closed in 229 days. There are 5 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of refinery is v1.21.0

            kandi-Quality Quality

              refinery has no bugs reported.

            kandi-Security Security

              refinery has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              refinery 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.

            kandi-Reuse Reuse

              refinery releases are available to install and integrate.
              Installation instructions are available. Examples and code snippets are not available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed refinery and discovered the below as its top functions. This is intended to give you an instant insight into refinery implemented functionality, and help decide if they suit your requirements.
            • Main entry point
            • compare compares two values .
            • NewConfig returns a new config object .
            • publicAddr returns the public version of the given configuration .
            • scan is used to scan all keys in a Redis
            • new redis peers
            • getEventTime extracts the time . Time from an etHeader
            • processTraceRequest processes trace requests
            • buildOptions builds redis . DialOption from the given config .
            • ConvertNumeric converts numeric value to a float64
            Get all kandi verified functions for this library.

            refinery Key Features

            No Key Features are available at this moment for refinery.

            refinery Examples and Code Snippets

            No Code Snippets are available at this moment for refinery.

            Community Discussions

            QUESTION

            google apps script get range somehow not working what am i doing wrong?
            Asked 2021-Jun-01 at 06:51

            somehow .getRange not working ?? works this way in every other script why not here ? Log is attached...

            Error is at line

            **

            "var days srcSheet.getRange("F" + i);"

            **

            ...

            ANSWER

            Answered 2021-Jun-01 at 06:51
            Modification points:
            • In the case of method getRange(a1Notation), the start number of A1Notation is 1. But in your script, the 1st number is 0. I think that this is the reason of your issue.
            • In your script, getValue and setValue are used in a loop. In this case, the process cost of the script becomes high. Ref
            Modified script 1:

            In this modification, your script is modified. In this case, please modify your script as follows.

            From:

            Source https://stackoverflow.com/questions/67783722

            QUESTION

            Google Script -> how to change this part of code, to get all columns?
            Asked 2021-May-31 at 12:10

            question is, how to change this part of the code, to get all columns from the array not only [0,1,2,3]

            this is the codeline:

            ...

            ANSWER

            Answered 2021-May-31 at 12:10
            Issue:

            Object.keys, when applied to an array, will return an array with the indexes of this array. If you're using it on this_table, you'll only when an array with 4 items, since that's the length of this_table.

            Because of this, you're only getting 4 rows for your "table".

            Solution:

            A easier and more efficient way to do this is to retrieve the values from your 4 desired columns at once, and use the different join on that:

            Source https://stackoverflow.com/questions/67770205

            QUESTION

            split row at specific time
            Asked 2021-Mar-13 at 21:58

            So I have a table from our time series sensor data for the plant. One of the sensor deals with movement of raw product on the belt (voltage / weight scale) before its processed into refinery. Whenever there is a delta (voltage of the belt less or more than normal / weight on belt (derived to every second) less or more than target for the 24 hour period (target ÷ 86,400 seconds ~ rounded to closest ton without decimal ) we capture it as a new event trigger and row in our warehouse database and move into data lake We need to find efficiency by work shift (day shift / grave shift) for time periods that cut across shift time

            Considering a 2400 tons target on a normal day and day shift between 5:00 AM to 5:00 PM and night shift vice versa, we want the following dataframe:

            starting dataframe row # event_start event_end operation_status tons_actual tons_target comment 1 2021-02-01 7:00 AM 2021-02-01 9:00 AM normal_run 197 200 2 2021-02-01 9:00 AM 2021-02-01 7:00 PM curtailed 700 1004 shift split here 3 2021-02-01 7:00 PM 2021-02-01 11:00 PM down_for_maintenance 0 301 4 2021-02-01 11:00 PM 2021-02-02 3:00 AM curtailed 320 402 5 2021-02-02 3:00 AM 2021-02-02 8:00 AM over_producing 600 502 shift split here 6 2021-02-02 8:00 AM 2021-02-02 11:00 AM normal_run 280 301 7 2021-02-02 11:00 AM 2021-02-04 4:00 PM broken_belt_unscheduled_loss 0 5323 multiple shift splits here

            to split rows at shift change hours like this:

            target dataframe row # event_start event_end operation_status tons_actual tons_target -------- 1 2021-02-01 7:00 AM 2021-02-01 9:00 AM normal_run 197 200 2.1 2021-02-01 9:00 AM 2021-02-01 5:00 PM curtailed 560 804 grave shift split 2.2 2021-02-01 5:00 PM 2021-02-01 7:00 PM curtailed 140 201 grave shift split 3 2021-02-01 7:00 PM 2021-02-01 11:00 PM down_for_maintenance 0 302 4 2021-02-01 11:00 PM 2021-02-02 3:00 AM curtailed 320 402 5.1 2021-02-02 3:00 AM 2021-02-02 5:00 AM over_producing 240 200 day shift split 5.2 2021-02-02 5:00 AM 2021-02-02 8:00 AM over_producing 360 302 day shift split 6 2021-02-02 8:00 AM 2021-02-02 11:00 AM normal_run 280 301 7.1 2021-02-02 11:00 AM 2021-02-02 5:00 PM broken_belt_unscheduled_loss 0 602 shift split 7.2 2021-02-02 5:00 PM 2021-02-03 5:00 AM broken_belt_unscheduled_loss 0 1205 shift split 7.3 2021-02-03 5:00 AM 2021-02-03 5:00 PM broken_belt_unscheduled_loss 0 1205 shift split 7.4 2021-02-03 5:00 PM 2021-02-04 5:00 AM broken_belt_unscheduled_loss 0 1205 shift split 7.5 2021-02-03 5:00 AM 2021-02-04 4:00 PM broken_belt_unscheduled_loss 0 1105 shift split

            so the end result can be then be df.groupby(sum : tons) per shift

            for a start, I know it needs some kind of array creating UDF inside an F.explode() function

            ...

            ANSWER

            Answered 2021-Mar-13 at 21:58

            You can use flatMap to transform a single row into multiple rows.

            Step 1: parse the date columns (if necessary, depends on the data source):

            Source https://stackoverflow.com/questions/66616834

            QUESTION

            Locust.io: RuntimeWarning: greenlet.greenlet size changed, may indicate binary incompatibility
            Asked 2020-Nov-26 at 02:45

            This is annoying, So I spent the past 15 hours trying to figure out why locust.io will not launch for me. On my mac machine, I am trying to get an example of locust running so I can begin my exploration of the package. I installed locust in my virtual env(python v3.7.7) using pip: pip install locust

            All packages installed successfully.

            here is the sample code:

            ...

            ANSWER

            Answered 2020-Oct-15 at 14:12

            QUESTION

            Suffle dataframe
            Asked 2020-Oct-06 at 00:11

            The columns present in the .ods file are: Fuel Name, Unit of Measure, Refinery, State, Year, January, February, March, April, May, June, July, August, September, October, November, December, Total. The columns for the months contain the corresponding sales figures for that month, and the Total column contains the sum of the values ​​for each month of the corresponding row. However, in some file conversions, the month and total values ​​shuffle n + k places to the right, starting from the first line, with k being incremented by 1 for each following line. More specifically, the first line suffers a shuffle of n squares, the second line suffers a shuffle of n + 1 squares, the third line suffers a shuffle of n + 2 squares ... the thirteenth line suffers a shuffle of 13 squares ( returning to the original configuration), and so on until the end of the file. Internally, you and your teammates have dubbed this problem "stair".

            First line example:

            Right: Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total

            1000 2500 1200 3000 1234 700 300 1000 0 800 2400 3500 17634

            With n = 4 shuffle:

            Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total

            800 2400 3500 17634 1000 2500 1200 3000 1234 700 300 1000 0

            With n = 1 shuffle:

            Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total

            17634 1000 2500 1200 3000 1234 700 300 1000 0 800 2400 3500

            Transforming the files into matrices, only with the columns above, we will have the following examples: Examples of desired patterns (correct matrix or step ladder):

            ...

            ANSWER

            Answered 2020-Oct-06 at 00:11
            
            import numpy as np
            
            
            matrizCorreta = np.array([ 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78], 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78], 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78], 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78], 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78], 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78], 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78], 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78], 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78],
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78], 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78], 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78]
             ])
            
            matrizInutilizavel_1 =  np.array([ 
             [11, 12, 78, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 
             [10, 11, 12, 78, 1, 2, 3, 4, 5, 6, 7, 8, 9], 
             [9, 10, 11, 12, 78, 1, 2, 3, 4, 5, 6, 7, 8], 
             [8, 9, 10, 11, 12, 2, 1, 78, 3, 4, 5, 6, 7], 
             [7, 8, 9, 10, 11, 12, 78, 1, 2, 3, 4, 5, 6], 
             [6, 7, 8, 9, 10, 11, 12, 78, 1, 2, 3, 4, 5], 
             [5, 6, 7, 8, 9, 10, 11, 12, 78, 1, 2, 3, 4], 
             [4, 5, 6, 7, 8, 9, 10, 11, 12, 78, 1, 2, 3], 
             [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78, 1, 2], 
             [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78, 1], 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78], 
             [78, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] 
             ])
            
            
            matrizInutilizavel_2 =  np.array([ 
             [11, 12, 1, 2, 78, 3, 4, 5, 6, 7, 8, 9, 10], 
             [10, 11, 12, 78, 1, 2, 3, 4, 5, 6, 7, 8, 9], 
             [9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 78],
             [8, 9, 10, 11, 12, 2, 1, 78, 3, 4, 5, 6, 7], 
             [7, 8, 9, 10, 11, 12, 78, 1, 2, 3, 4, 5, 6], 
             [6, 7, 8, 9, 10, 11, 12, 78, 1, 2, 3, 4, 5], 
             [5, 6, 7, 8, 9, 10, 11, 12, 78, 1, 2, 3, 4], 
             [4, 5, 6, 7, 8, 9, 10, 11, 12, 78, 1, 2, 3], 
             [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78, 1, 2], 
             [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78, 1], 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78], 
             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 78] 
             ])
            
            
            
            ### função recebe uma array 2d qualquer e retorna uma nova array ordenada
            def verificacaoMatriz (matriz):
                nova_matriz = []
                ## numero de linhas da matriz
                rows = matriz.shape[0]
                #Número de colunas da matriz
                cols = matriz.shape[1]
                #para todo X no range de 0 até o numero de itens - 1
                for x in range(0,rows-1):
                     #para todo Y no range de 0 até o numero de itens - 1
                    for y in range(0,cols-1):
                        ## Se o valor atual da matriz (linha,coluna) for igual ao próximo valor da diagonal (linha+1,coluna + 1)
                        ## Exemplo, valor (0,0) contra (1,1), faça:
                        if(matriz[x,y] == matriz[x+1,y+1]):
                            ### Ordena todas as linhas da matriz usando a função sort do numpy
                            nova_matriz = np.sort(matriz)
                ### se a variavel nova matriz está vazia, significa que a matriz estava correta e não precisou de ordenação
                ### Então só atribuo a matriz original a esta
                if not len(nova_matriz):
                    nova_matriz = matriz
                ### Verifica se a array está em ordem            
                is_sorted = lambda a: np.all(a[:-1] <= a[1:])
                if(is_sorted(nova_matriz)==True):
                    print("Matriz Correta")
                else:
                    print("Matriz Inutilizável")
                return nova_matriz        
            
            
            
            #### Testando a matriz Correta
            matriz1 = verificacaoMatriz(matrizCorreta)
            print("Matriz1",matriz1)
            
            #### Testando a matriz inutil1 
            matriz2 = verificacaoMatriz(matrizInutilizavel_1)
            print("Matriz2",matriz2)
            
            
            #### Testando a matriz inutil2
            matriz3 = verificacaoMatriz(matrizInutilizavel_2)
            print("Matriz3",matriz3)
            

            Source https://stackoverflow.com/questions/64178144

            QUESTION

            Validate the row data in one pyspark Dataframe matched in another Dataframe
            Asked 2020-Feb-17 at 13:47

            I have 2 Pyspark Dataframe df1,df2. Both df1 and df2 contains millions of records.

            df1 is like:

            ...

            ANSWER

            Answered 2020-Feb-17 at 13:47

            Using levenshtein-distance with left join you can do something like this:

            Source https://stackoverflow.com/questions/60262477

            QUESTION

            LINQ Subquery Where Clause could not be translated
            Asked 2020-Jan-27 at 11:31

            I am converting this query to linq in EF Core 2.2 but I could not find any correct way:

            ...

            ANSWER

            Answered 2020-Jan-27 at 10:38

            Seems to be one of the (many) EFC 2.2 query translator bugs/defects/shortcomings. Works as expected in EFC 3.1.

            From all the "query patterns" (as they call them), the only one working I was able to found is to push the predicate into join clause, e.g. replace

            Source https://stackoverflow.com/questions/59926956

            QUESTION

            Playing a simulation in fast-forward
            Asked 2020-Jan-15 at 08:42

            I am working a simple game where users create structures in a sector, which is a 10x10 grid. Some structures generate resources and some consume resources. The sector itself might contain some resources outside of any structure. The generators and consumers are related. For example, a well might be generating water, then an splitter be consuming water and making hydrogen and oxygen, while a refinery is consuming hydrogen and oxygen and making rocket fuel, etc.

            The rate at which they generate or consume resources can vary by structure - I call this the tick rate. Each time a consumer ticks, it will first attempt to extract those resources from the structures that surround it in the sector. If there are not enough, it will try to get them from the sector's storage. If it is still not enough, the structure will stop. Structures hold the resources that they generate up to some maximum. Once they are full, they will not generate more until some are consumed. If a structure is stopped, it will also not generate more resources, but the resources it already has can still be used by another adjacent structure.

            It is not uncommon that there are patterns. For example, if the well is very slow, the splitter will turn off when the well runs out of water, and then the refinery will turn off when the splitter runs out of gases. Then when the well generates again, everything will turn back on.

            When the user is playing a sector, I tick the sector continuously at the resolution of shortest tick rate of the sector's structures. This works fine. The pseudo-code looks like this:

            ...

            ANSWER

            Answered 2020-Jan-15 at 08:42

            Step 1: Convert the raw data into "graph of nodes" form, where each node represents a machine, and producers are at the bottom and consumers are at the top. For example it might look like:

            Source https://stackoverflow.com/questions/59742268

            QUESTION

            Classification of data in alphabetic order in r
            Asked 2020-Jan-07 at 12:24

            I have a sample data below.

            ...

            ANSWER

            Answered 2020-Jan-07 at 11:49

            In your data frame, the levels of the Fluid type are not in alphabetical order

            Source https://stackoverflow.com/questions/59627791

            QUESTION

            Data Profiling - How to count nulls, NaNs and empty string values?
            Asked 2019-Oct-28 at 12:52

            I am new to pyspark and I have this example dataset:

            ...

            ANSWER

            Answered 2019-Oct-28 at 12:52

            you could do the following :

            first change all Null/None values into Panda NaN's

            Source https://stackoverflow.com/questions/58591201

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

            Vulnerabilities

            No vulnerabilities reported

            Install refinery

            Refinery is designed to sit within your infrastructure where all sources of Honeycomb events (aka spans if you're doing tracing) can reach it. A standard deployment will have a cluster of two or more Refinery processes accessible via a separate load balancer. Refinery processes must be able to communicate with each other to concentrate traces on single servers. Within your application (or other Honeycomb event sources) you would configure the API Host to be http(s)://load-balancer/. Everything else remains the same (api key, dataset name, etc. - all that lives with the originating client).

            Support

            The default logging level of warn is almost entirely silent. The debug level emits too much data to be used in production, but contains excellent information in a pre-production environment. Setting the logging level to debug during initial configuration will help understand what's working and what's not, but when traffic volumes increase it should be set to warn.
            Find more information at:

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            CLONE
          • HTTPS

            https://github.com/honeycombio/refinery.git

          • CLI

            gh repo clone honeycombio/refinery

          • sshUrl

            git@github.com:honeycombio/refinery.git

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