fuzzyjoin | Efficient Parallel Set-Similarity Joins Using MapReduce

 by   TonyApuzzo Java Version: Current License: Apache-2.0

kandi X-RAY | fuzzyjoin Summary

kandi X-RAY | fuzzyjoin Summary

fuzzyjoin is a Java library. fuzzyjoin 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.

I wasn't able to find this project hosted at the original location anymore, so I published it here. All credit goes to the original authors. Fork of Efficient Parallel Set-Similarity Joins Using MapReduce. Rares Vernica, Michael J. Carey, Chen Li SIGMOD 2010.

            kandi-support Support

              fuzzyjoin has a low active ecosystem.
              It has 4 star(s) with 3 fork(s). There are 1 watchers for this library.
              It had no major release in the last 6 months.
              fuzzyjoin has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of fuzzyjoin is current.

            kandi-Quality Quality

              fuzzyjoin has no bugs reported.

            kandi-Security Security

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

            kandi-License License

              fuzzyjoin 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

              fuzzyjoin 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 are not available. Examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed fuzzyjoin and discovered the below as its top functions. This is intended to give you an instant insight into fuzzyjoin implemented functionality, and help decide if they suit your requirements.
            • Map the record to the output
            • Maps the input value to the output
            • Map the input value
            • Set up the configuration
            • Set up the job configuration
            • Reduces values into the output collector
            • Reduces values by key
            • Reduces values to the output
            • Reduces values to the specified values
            • Reduces values to values
            • Performs a fuzzy reduce on the input values
            • Reduces a set of input values to the output
            • Performs the reduction
            • Computes the count of values
            • Reduces the values
            • Test program
            • Configure the fuzzy join driver
            • Main entry point for the RDB
            • The main method
            • Move to the next separator
            • Moves to the next token
            • Serialize a token
            • Sets the job - 1
            • Main entry point for testing
            • Entry point for debugging
            • Main entry point to the tokens file
            • Maps a record to the output
            • Command - line tool
            Get all kandi verified functions for this library.

            fuzzyjoin Key Features

            No Key Features are available at this moment for fuzzyjoin.

            fuzzyjoin Examples and Code Snippets

            No Code Snippets are available at this moment for fuzzyjoin.

            Community Discussions


            Multiple conditions using element in df matching a colname in lookup table to merge 3 dataframes
            Asked 2021-Jun-13 at 20:28

            I have three large dataframes and I want to append some of the elements from one onto another based on several criteria. I looked up similar questions in Stack Overflow but they don't seem to work for my dataframe format (or I'm not skilled enough to adapt it properly).

            What needs to happen is:

            1. Filter by sex in maindf1
            2. Search for the same ZCTA value in maindf1 in a rowname (first column) in maledflookup
            3. Also search for the right age strata from a row in maindf1 in the column name of maledflookup
            4. Add a new column of data to maindf1 row with matching ZCTA that has the census population value for that sex and age strata taken from maledflookup
            5. Repeat with femaledflookup
            6. End result is maindf1 having a censuspop value for every row that was matched by sex, ZCTA, and age strata

            maindf1 is raw data where each row is an individual and columns are survey responses or collected data on individuals

            The lookup table from the census website I had to use is in weird formatting so the easiest solution for me to fix one of the issues with it was to separate the lookup tables by sex first.

            I had no luck in writing successful code as I'm not very experienced with coding in R yet. I tried some for & if loops and failed at adapting fuzzyjoin code for this task. I appreciate your help!

            Example data:



            Answered 2021-Jun-12 at 17:56

            Use left_join from tidyverse and a properly formatted lookup table:

            Source https://stackoverflow.com/questions/67951430


            test if words are in a string (grepl, fuzzyjoin?)
            Asked 2021-Jun-07 at 17:20

            I need to do a match and join on two data frames if the string from two columns of one data frame are contained in the string of a column from a second data frame.

            Example dataframe:



            Answered 2021-Jun-07 at 14:20

            The documentation says that match_fun should be a "Vectorized function given two columns, returning TRUE or FALSE as to whether they are a match." It's not TRUE or FALSE, it's a function that returns TRUE or FALSE. If we switch your order, we can use stringr::str_detect, which does return TRUE or FALSE as required.

            Source https://stackoverflow.com/questions/67873046


            Modify a vector based on a vector of regular expressions (regex) using (if possible) a functional approach
            Asked 2021-May-21 at 16:55

            I have a dataframe with some columns that I want to modify depending on whether they match some patterns included in a vector with regular expressions



            Answered 2021-May-20 at 22:21

            One option utilizing stringr and purrr could be:

            Source https://stackoverflow.com/questions/67628146


            merge two data.frame using a column with the same strings but in different order
            Asked 2021-Apr-28 at 10:43

            I am trying to merge two data.frames using a column that contains strings. The strings in the two columns are names, unfortunately, they are not in the same order. In the example below, names in df_1 have the structure "name"+"midname"+"surname1"+"surname2" while in df_2 the structure is "surname1"+"surname2"+"name"+"midname".

            I first tried to do a fuzzy merge using the names. However, it doesn't solve the problem since there are still non-zero matches between totally different names. Additionally, it is non-trivial to define a cutting point that can define when a name is totally different from another. I was also expecting a higher degree of similarity between names with reverse order (i.e., (name+midname) + (surname1+surname2) in a different order).

            Do you have a better way to merge the two data.frame using these names in a different order? Thanks in advance.



            Answered 2021-Apr-28 at 10:43

            You can strsplit to individual names, sort them and paste. Then use match.

            Source https://stackoverflow.com/questions/67297937


            Join data objects by date but with different intervals
            Asked 2021-Apr-20 at 12:05

            I have ran into this issue and I really have no clue how to do it. I have two data.frames, both with date columns. However, the first one, which is a big object, contains measurements each 3 seconds, while the second contains measurements each 10 minutes. I want to include the measurement variable of object 2 into object 1 (something like a left_join or merge) by the date variable. My data looks like this (df1):

            date_time measurement1 yyyy-mm-dd HH:MM:03 val1 yyyy-mm-dd HH:MM:06 val2


            date_time measurement2 yyyy-mm-dd HH:10:00 val1 yyyy-mm-dd HH:20:00 val2

            I hope that is enough info, otherwise please comment. I have explored foverlapse and fuzzyjoin but without success.

            Thank you in advance

            Here is what I have in a bit more detail (df1):

            date_time measurement1 05/06/2018 0:00:03 73 05/06/2018 0:00:06 73.5 05/06/2018 0:00:09 48.5 05/06/2018 0:00:12 50.7 05/06/2018 0:00:15 80 05/06/2018 0:00:18 81

            Data continue for a number of months every time each 3 seconds


            date_time measurement2 05/06/2018 0:00:00 110 05/06/2018 0:10:00 120 05/06/2018 0:20:00 180

            What I want is this:


            date_time measurement1 measurement2 05/06/2018 0:00:03 73 110 05/06/2018 0:00:06 73.5 110 05/06/2018 0:00:09 48.5 110 05/06/2018 0:00:12 50.7 110 05/06/2018 0:00:15 80 110 05/06/2018 0:00:18 81 110

            I hope now is clearer, by the way, there might be an issue with tables, I am using the format I am told by Stack overflow and I can see the tables being produced in the review, but then the format is lost when I submit.

            Thank you



            Answered 2021-Apr-20 at 12:05

            Every minute has 20 observations if those observations occur every 3 seconds. Hence, there are 200 observations for every 10 minute interval. If your data is complete, then it would suffice that you stretch out your seconds 10-minute-interval observations accordingly, i.e. you copy every 10-minute-interval value 200 times next to the 3-second-interval values.

            Try the following and tell me what you get

            Source https://stackoverflow.com/questions/67169913


            Merging 2 data frames with placeholders in multiple positions in df1, and placeholders filled in df2
            Asked 2021-Mar-19 at 17:12

            I have two data frames; (DF 1) that has rows with both variables that have "wildcards" in different locations of the string as well as variables with no "wildcards", and (DF 2) that has multiple rows with variables from DF 1 but the "wildcard" filled in.

            DF 1



            Answered 2021-Mar-19 at 17:03

            You need a combination of utils::glob2rz and fuzzyjoin::regex_*_join:

            fuzzyjoin::regex_*_join requires true-regex patterns, but your patterns appear to be more "glob"-style wildcards. Luckily, we can easily convert from the latter to the former in base R:

            Source https://stackoverflow.com/questions/66712451


            fuzzy_left_join with match_fun %in%
            Asked 2021-Mar-03 at 19:21

            Some data



            Answered 2021-Mar-03 at 19:21

            If we want to do a partial match with the word before the / in the 'url' with the 'string' column in 'lookup_df', we could extract that substring as a new column and then do a regex_left_join

            Source https://stackoverflow.com/questions/66463306


            Function to `interval_left_join` multiple dataframes
            Asked 2021-Mar-02 at 11:49

            I have several dataframes I want to interval_left_join. I could in theory join the dataframes step-by-step but would prefer a function to perform the joins in one go:




            Answered 2021-Mar-02 at 11:49

            Perform only the join in Reduce, v2, v3, v4 columns can be summarised after the join.

            Source https://stackoverflow.com/questions/66437682


            How to fuzzyjoin several dataframes in one go using IRanges
            Asked 2021-Feb-28 at 13:50

            I need to join several dataframes based on inexact matching, which can be achieved using the fuzzyjoin and the IRanges packages:




            Answered 2021-Feb-28 at 13:45

            Put the dataframes in a list and join the dataframes with Reduce.

            Source https://stackoverflow.com/questions/66409697


            Joining by multiple columns with stringdist_join
            Asked 2020-Dec-27 at 22:43

            I have two dataframes, where column x can have typos and column y is always correct. I can't figure out why joining by multiple columns with stringdist gives these pairs:



            Answered 2020-Dec-27 at 15:24

            cbind can reproduce your desired output.

            Source https://stackoverflow.com/questions/65467009

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


            No vulnerabilities reported

            Install fuzzyjoin

            You can download it from GitHub.
            You can use fuzzyjoin like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the fuzzyjoin component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .


            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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