fuzzyjoin | Efficient Parallel Set-Similarity Joins Using MapReduce
kandi X-RAY | fuzzyjoin Summary
kandi X-RAY | fuzzyjoin Summary
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.
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Top functions reviewed by kandi - BETA
- 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
fuzzyjoin Key Features
fuzzyjoin Examples and Code Snippets
Community Discussions
Trending Discussions on fuzzyjoin
QUESTION
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:
- Filter by sex in maindf1
- Search for the same ZCTA value in maindf1 in a rowname (first column) in maledflookup
- Also search for the right age strata from a row in maindf1 in the column name of maledflookup
- 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
- Repeat with femaledflookup
- 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:
...ANSWER
Answered 2021-Jun-12 at 17:56Use left_join
from tidyverse and a properly formatted lookup table:
QUESTION
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:
...ANSWER
Answered 2021-Jun-07 at 14:20The 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.
QUESTION
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
...ANSWER
Answered 2021-May-20 at 22:21One option utilizing stringr
and purrr
could be:
QUESTION
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.
...ANSWER
Answered 2021-Apr-28 at 10:43You can strsplit
to individual names, sort
them and paste
. Then use match
.
QUESTION
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 val2df2:
date_time measurement2 yyyy-mm-dd HH:10:00 val1 yyyy-mm-dd HH:20:00 val2I 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 81Data continue for a number of months every time each 3 seconds
df2:
date_time measurement2 05/06/2018 0:00:00 110 05/06/2018 0:10:00 120 05/06/2018 0:20:00 180What I want is this:
df:
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 110I 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
...ANSWER
Answered 2021-Apr-20 at 12:05Every 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
QUESTION
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
...ANSWER
Answered 2021-Mar-19 at 17:03You 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:
QUESTION
Some data
...ANSWER
Answered 2021-Mar-03 at 19:21If 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
QUESTION
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:
Data:
...ANSWER
Answered 2021-Mar-02 at 11:49Perform only the join in Reduce
, v2
, v3
, v4
columns can be summarised after the join.
QUESTION
I need to join several dataframes based on inexact matching, which can be achieved using the fuzzyjoin
and the IRanges
packages:
Data:
...ANSWER
Answered 2021-Feb-28 at 13:45Put the dataframes in a list and join the dataframes with Reduce
.
QUESTION
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:
ANSWER
Answered 2020-Dec-27 at 15:24cbind
can reproduce your desired output.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install fuzzyjoin
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 .
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