⚠️ Warning: This is a draft ⚠️

This means it might contain formatting issues, incorrect code, conceptual problems, or other severe issues.

If you want to help to improve and eventually enable this page, please fork RosettaGit's repository and open a merge request on GitHub.

An [[wp:Join_(SQL)#Inner_join|inner join]] is an operation that combines two data tables into one table, based on matching column values. The simplest way of implementing this operation is the [[wp:Nested loop join|nested loop join]] algorithm, but a more scalable alternative is the [[wp:hash join|hash join]] algorithm.

Implement the "hash join" algorithm, and demonstrate that it passes the test-case listed below.

You should represent the tables as data structures that feel natural in your programming language.

The "hash join" algorithm consists of two steps:

'''Hash phase:''' Create a [[wp:Multimap|multimap]] from one of the two tables, mapping from each join column value to all the rows that contain it.

#* The multimap must support hash-based lookup which scales better than a simple linear search, because that's the whole point of this algorithm. #* Ideally we should create the multimap for the ''smaller'' table, thus minimizing its creation time and memory size.

'''Join phase:''' Scan the other table, and find matching rows by looking in the multimap created before.

In pseudo-code, the algorithm could be expressed as follows:

'''let''' ''A'' = the first input table (or ideally, the larger one) '''let''' ''B'' = the second input table (or ideally, the smaller one) '''let''' ''j_A'' = the join column ID of table ''A'' '''let''' ''j_B'' = the join column ID of table ''B'' '''let''' ''M_B'' = a multimap for mapping from single values to multiple rows of table ''B'' (starts out empty) '''let''' ''C'' = the output table (starts out empty)

'''for each''' row ''b'' '''in''' table ''B''''':''' '''place''' ''b'' '''in''' multimap ''M_B'' under key ''b''(''j_B'')

'''for each''' row ''a'' '''in''' table ''A''''':''' '''for each''' row ''b'' '''in''' multimap ''M_B'' under key ''a''(''j_A'')''':''' '''let''' ''c'' = the concatenation of row ''a'' and row ''b'' '''place''' row ''c'' in table ''C''

{| class="wikitable" |- ! Input ! Output |- |

{| style="border:none; border-collapse:collapse;" |- | style="border:none" | ''A'' = | style="border:none" |

{| class="wikitable" |- ! Age !! Name |- | 27 || Jonah |- | 18 || Alan |- | 28 || Glory |- | 18 || Popeye |- | 28 || Alan |}

{| class="wikitable" |- ! Character !! Nemesis |- | Jonah || Whales |- | Jonah || Spiders |- | Alan || Ghosts |- | Alan || Zombies |- | Glory || Buffy |}

| style="border:none" | ''j_B'' = | style="border:none" | Character (i.e. column 0) |}

{| class="wikitable" style="margin-left:1em" |- ! A.Age !! A.Name !! B.Character !! B.Nemesis |- | 27 || Jonah || Jonah || Whales |- | 27 || Jonah || Jonah || Spiders |- | 18 || Alan || Alan || Ghosts |- | 18 || Alan || Alan || Zombies |- | 28 || Glory || Glory || Buffy |- | 28 || Alan || Alan || Ghosts |- | 28 || Alan || Alan || Zombies |}

The order of the rows in the output table is not significant.

If you're using numerically indexed arrays to represent table rows (rather than referring to columns by name), you could represent the output rows in the form [[27, "Jonah"], ["Jonah", "Whales"]].

AppleScript

Native AppleScript records lack introspection, but from Yosemite onwards we can read and write them a little more flexibly through the Foundation classes. The vertical bars distinguish AppleScript reserved words ('''name''' and '''character''' here) from field name literal strings.

use framework "Foundation" -- Yosemite onwards, for record-handling functions

-- HASH JOIN -----------------------------------------------------------------

-- hashJoin :: [Record] -> [Record] -> String -> [Record]
on hashJoin(tblA, tblB, strJoin)
    set {jA, jB} to splitOn("=", strJoin)

    script instanceOfjB
        on |λ|(a, x)
            set strID to keyValue(x, jB)

            set maybeInstances to keyValue(a, strID)
            if maybeInstances is not missing value then
                updatedRecord(a, strID, maybeInstances & {x})
            else
                updatedRecord(a, strID, [x])
            end if
        end |λ|
    end script

    set M to foldl(instanceOfjB, {name:"multiMap"}, tblB)

    script joins
        on |λ|(a, x)
            set matches to keyValue(M, keyValue(x, jA))
            if matches is not missing value then
                script concat
                    on |λ|(row)
                        x & row
                    end |λ|
                end script

                a & map(concat, matches)
            else
                a
            end if
        end |λ|
    end script

    foldl(joins, {}, tblA)
end hashJoin

-- TEST ----------------------------------------------------------------------
on run
    set lstA to [¬
        {age:27, |name|:"Jonah"}, ¬
        {age:18, |name|:"Alan"}, ¬
        {age:28, |name|:"Glory"}, ¬
        {age:18, |name|:"Popeye"}, ¬
        {age:28, |name|:"Alan"}]

    set lstB to [¬
        {|character|:"Jonah", nemesis:"Whales"}, ¬
        {|character|:"Jonah", nemesis:"Spiders"}, ¬
        {|character|:"Alan", nemesis:"Ghosts"}, ¬
        {|character|:"Alan", nemesis:"Zombies"}, ¬
        {|character|:"Glory", nemesis:"Buffy"}, ¬
        {|character|:"Bob", nemesis:"foo"}]

    hashJoin(lstA, lstB, "name=character")
end run


-- RECORD FUNCTIONS ----------------------------------------------------------

-- keyValue :: String -> Record -> Maybe a
on keyValue(rec, strKey)
    set ca to current application
    set v to (ca's NSDictionary's dictionaryWithDictionary:rec)'s ¬
        objectForKey:strKey
    if v is not missing value then
        item 1 of ((ca's NSArray's arrayWithObject:v) as list)
    else
        missing value
    end if
end keyValue

-- updatedRecord :: Record -> String -> a -> Record
on updatedRecord(rec, strKey, varValue)
    set ca to current application
    set nsDct to (ca's NSMutableDictionary's dictionaryWithDictionary:rec)
    nsDct's setValue:varValue forKey:strKey
    item 1 of ((ca's NSArray's arrayWithObject:nsDct) as list)
end updatedRecord


-- GENERIC FUNCTIONS ---------------------------------------------------------

-- foldl :: (a -> b -> a) -> a -> [b] -> a
on foldl(f, startValue, xs)
    tell mReturn(f)
        set v to startValue
        set lng to length of xs
        repeat with i from 1 to lng
            set v to |λ|(v, item i of xs, i, xs)
        end repeat
        return v
    end tell
end foldl

-- map :: (a -> b) -> [a] -> [b]
on map(f, xs)
    tell mReturn(f)
        set lng to length of xs
        set lst to {}
        repeat with i from 1 to lng
            set end of lst to |λ|(item i of xs, i, xs)
        end repeat
        return lst
    end tell
end map

-- Lift 2nd class handler function into 1st class script wrapper
-- mReturn :: Handler -> Script
on mReturn(f)
    if class of f is script then
        f
    else
        script
            property |λ| : f
        end script
    end if
end mReturn

-- splitOn :: Text -> Text -> [Text]
on splitOn(strDelim, strMain)
    set {dlm, my text item delimiters} to {my text item delimiters, strDelim}
    set lstParts to text items of strMain
    set my text item delimiters to dlm
    return lstParts
end splitOn

{{age:27, |name|:"Jonah", |character|:"Jonah", nemesis:"Whales"},
{age:27, |name|:"Jonah", |character|:"Jonah", nemesis:"Spiders"},
{age:18, |name|:"Alan", |character|:"Alan", nemesis:"Ghosts"},
{age:18, |name|:"Alan", |character|:"Alan", nemesis:"Zombies"},
{age:28, |name|:"Glory", |character|:"Glory", nemesis:"Buffy"},
{age:28, |name|:"Alan", |character|:"Alan", nemesis:"Ghosts"},
{age:28, |name|:"Alan", |character|:"Alan", nemesis:"Zombies"}}

AWK


# syntax: GAWK -f HASH_JOIN.AWK [-v debug={0|1}] TABLE_A TABLE_B
#
# sorting:
#   PROCINFO["sorted_in"] is used by GAWK
#   SORTTYPE is used by Thompson Automation's TAWK
#
BEGIN {
    FS = ","
    PROCINFO["sorted_in"] = "@ind_str_asc" ; SORTTYPE = 1
    if (ARGC-1 != 2) {
      print("error: incorrect number of arguments") ; errors++
      exit # go to END
    }
}
{   if (NR == FNR) { # table A
      if (FNR == 1) {
        a_head = prefix_column_names("A")
        next
      }
      a_arr[$2][$1] = $0 # [name][age]
    }
    if (NR != FNR) { # table B
      if (FNR == 1) {
        b_head = prefix_column_names("B")
        next
      }
      b_arr[$1][$2] = $0 # [character][nemesis]
    }
}
END {
    if (errors > 0) { exit(1) }
    if (debug == 1) {
      dump_table(a_arr,a_head)
      dump_table(b_arr,b_head)
    }
    printf("%s%s%s\n",a_head,FS,b_head) # table heading
    for (i in a_arr) {
      if (i in b_arr) {
        for (j in a_arr[i]) {
          for (k in b_arr[i]) {
            print(a_arr[i][j] FS b_arr[i][k]) # join table A & table B
          }
        }
      }
    }
    exit(0)
}
function dump_table(arr,heading,  i,j) {
    printf("%s\n",heading)
    for (i in arr) {
      for (j in arr[i]) {
        printf("%s\n",arr[i][j])
      }
    }
    print("")
}
function prefix_column_names(p,  tmp) {
    tmp = p "." $0
    gsub(/,/,"&" p ".",tmp)
    return(tmp)
}

TABLE_A input:


Age,Name
27,Jonah
18,Alan
28,Glory
18,Popeye
28,Alan

TABLE_B input:


Character,Nemesis
Jonah,Whales
Jonah,Spiders
Alan,Ghosts
Alan,Zombies
Glory,Buffy


A.Age,A.Name,B.Character,B.Nemesis
18,Alan,Alan,Ghosts
18,Alan,Alan,Zombies
28,Alan,Alan,Ghosts
28,Alan,Alan,Zombies
28,Glory,Glory,Buffy
27,Jonah,Jonah,Spiders
27,Jonah,Jonah,Whales

Bracmat

This solution creates a hash table for the smaller relation in the function join. This function takes as arguments the smallest table, the biggest table and then three pieces of code: two patterns that describe each table's field order and code that generates one row of output. These pieces of code are inserted in a fixed skeleton of code using macro substitution.

(     (27.Jonah)
      (18.Alan)
      (28.Glory)
      (18.Popeye)
      (28.Alan)
  : ?table-A
&     (Jonah.Whales)
      (Jonah.Spiders)
      (Alan.Ghosts)
      (Alan.Zombies)
      (Glory.Buffy)
  : ?table-B
& new$hash:?H
& !table-A:? [?lenA
& !table-B:? [?lenB
& ( join
  =     smalltab bigtab smallschema bigschema joinschema
      , key val val2 keyval2
    .     !arg
        : (?smalltab.?bigtab.(=?smallschema.?bigschema.?joinschema))
      & :?rel
      & !(
         ' (   whl
             ' ( !smalltab:$smallschema ?smalltab
               & (H..insert)$(!key.!val)
               )
           &   whl
             ' ( !bigtab:$bigschema ?bigtab
               & (   (H..find)$!key:?keyval2
                   &   whl
                     ' ( !keyval2:(?key.?val2) ?keyval2
                       & $joinschema !rel:?rel
                       )
                 |
                 )
               )
           )
         )
      & !rel
  )
&   out
  $ ( join
    $ (   !lenA:~<!lenB
        & ( !table-B
          . !table-A
          . (
            = (?key.?val).(?val.?key).!val.!key.!val2
            )
          )
      | ( !table-A
        . !table-B
        . (=(?val.?key).(?key.?val).!val2.!key.!val)
        )
      )
    )
&
);

Output:

  (28.Alan.Ghosts)
  (28.Alan.Zombies)
  (28.Glory.Buffy)
  (18.Alan.Ghosts)
  (18.Alan.Zombies)
  (27.Jonah.Whales)
  (27.Jonah.Spiders)

C++

#include <iostream>
#include <string>
#include <vector>
#include <unordered_map>

using tab_t = std::vector<std::vector<std::string>>;
tab_t tab1 {
// Age  Name
  {"27", "Jonah"}
, {"18", "Alan"}
, {"28", "Glory"}
, {"18", "Popeye"}
, {"28", "Alan"}
};

tab_t tab2 {
// Character  Nemesis
  {"Jonah", "Whales"}
, {"Jonah", "Spiders"}
, {"Alan", "Ghosts"}
, {"Alan", "Zombies"}
, {"Glory", "Buffy"}
};

std::ostream& operator<<(std::ostream& o, const tab_t& t) {
  for(size_t i = 0; i < t.size(); ++i) {
    o << i << ":";
    for(const auto& e : t[i])
      o << '\t' << e;
    o << std::endl;
  }
  return o;
}

tab_t Join(const tab_t& a, size_t columna, const tab_t& b, size_t columnb) {
  std::unordered_multimap<std::string, size_t> hashmap;
  // hash
  for(size_t i = 0; i < a.size(); ++i) {
    hashmap.insert(std::make_pair(a[i][columna], i));
  }
  // map
  tab_t result;
  for(size_t i = 0; i < b.size(); ++i) {
    auto range = hashmap.equal_range(b[i][columnb]);
    for(auto it = range.first; it != range.second; ++it) {
      tab_t::value_type row;
      row.insert(row.end() , a[it->second].begin() , a[it->second].end());
      row.insert(row.end() , b[i].begin()          , b[i].end());
      result.push_back(std::move(row));
    }
  }
  return result;
}

int main(int argc, char const *argv[])
{
  using namespace std;
  int ret = 0;
  cout << "Table A: "       << endl << tab1 << endl;
  cout << "Table B: "       << endl << tab2 << endl;
  auto tab3 = Join(tab1, 1, tab2, 0);
  cout << "Joined tables: " << endl << tab3 << endl;
  return ret;
}

Table A:
0:  27  Jonah
1:  18  Alan
2:  28  Glory
3:  18  Popeye
4:  28  Alan

Table B:
0:  Jonah Whales
1:  Jonah Spiders
2:  Alan  Ghosts
3:  Alan  Zombies
4:  Glory Buffy

Joined tables:
0:  27  Jonah Jonah Whales
1:  27  Jonah Jonah Spiders
2:  28  Alan  Alan  Ghosts
3:  18  Alan  Alan  Ghosts
4:  28  Alan  Alan  Zombies
5:  18  Alan  Alan  Zombies
6:  28  Glory Glory Buffy

C#

;using LINQ to Objects

using System;
using System.Collections.Generic;
using System.Linq;

namespace HashJoin
{
    public class AgeName
    {
        public AgeName(byte age, string name)
        {
            Age = age;
            Name = name;
        }
        public byte Age { get; private set; }
        public string Name { get; private set; }
    }

    public class NameNemesis
    {
        public NameNemesis(string name, string nemesis)
        {
            Name = name;
            Nemesis = nemesis;
        }
        public string Name { get; private set; }
        public string Nemesis { get; private set; }
    }

    public class DataContext
    {
        public DataContext()
        {
            AgeName = new List<AgeName>();
            NameNemesis = new List<NameNemesis>();
        }
        public List<AgeName> AgeName { get; set; }
        public List<NameNemesis> NameNemesis { get; set; }
    }

    public class AgeNameNemesis
    {
        public AgeNameNemesis(byte age, string name, string nemesis)
        {
            Age = age;
            Name = name;
            Nemesis = nemesis;
        }
        public byte Age { get; private set; }
        public string Name { get; private set; }
        public string Nemesis { get; private set; }
    }

    class Program
    {
        public static void Main()
        {
            var data = GetData();
            var result = ExecuteHashJoin(data);
            WriteResultToConsole(result);
        }

        private static void WriteResultToConsole(List<AgeNameNemesis> result)
        {
            result.ForEach(ageNameNemesis => Console.WriteLine("Age: {0}, Name: {1}, Nemesis: {2}",
                ageNameNemesis.Age, ageNameNemesis.Name, ageNameNemesis.Nemesis));
        }

        private static List<AgeNameNemesis> ExecuteHashJoin(DataContext data)
        {
            return (data.AgeName.Join(data.NameNemesis,
                ageName => ageName.Name, nameNemesis => nameNemesis.Name,
                (ageName, nameNemesis) => new AgeNameNemesis(ageName.Age, ageName.Name, nameNemesis.Nemesis)))
                .ToList();
        }

        private static DataContext GetData()
        {
            var context = new DataContext();

            context.AgeName.AddRange(new [] {
                    new AgeName(27, "Jonah"),
                    new AgeName(18, "Alan"),
                    new AgeName(28, "Glory"),
                    new AgeName(18, "Popeye"),
                    new AgeName(28, "Alan")
                });

            context.NameNemesis.AddRange(new[]
            {
                new NameNemesis("Jonah", "Whales"),
                new NameNemesis("Jonah", "Spiders"),
                new NameNemesis("Alan", "Ghosts"),
                new NameNemesis("Alan", "Zombies"),
                new NameNemesis("Glory", "Buffy")
            });

            return context;
        }
    }
}


Age: 27, Name: Jonah, Nemesis: Whales
Age: 27, Name: Jonah, Nemesis: Spiders
Age: 18, Name: Alan, Nemesis: Ghosts
Age: 18, Name: Alan, Nemesis: Zombies
Age: 28, Name: Glory, Nemesis: Buffy
Age: 28, Name: Alan, Nemesis: Ghosts
Age: 28, Name: Alan, Nemesis: Zombies

Clojure


(defn hash-join [table1 col1 table2 col2]
  (let [hashed (group-by col1 table1)]
    (flatten
      (for [r table2]
        (for [s (hashed (col2 r))]
          (merge s r))))))

(def s '({:age 27 :name "Jonah"}
         {:age 18 :name "Alan"}
         {:age 28 :name "Glory"}
         {:age 18 :name "Popeye"}
         {:age 28 :name "Alan"}))

(def r '({:nemesis "Whales" :name "Jonah"}
         {:nemesis "Spiders" :name "Jonah"}
         {:nemesis "Ghosts" :name "Alan"}
         {:nemesis "Zombies" :name "Alan"}
         {:nemesis "Buffy" :name "Glory"}))

(pprint (sort-by :name (hash-join s :name r :name)))


({:nemesis "Ghosts", :age 18, :name "Alan"}
 {:nemesis "Ghosts", :age 28, :name "Alan"}
 {:nemesis "Zombies", :age 18, :name "Alan"}
 {:nemesis "Zombies", :age 28, :name "Alan"}
 {:nemesis "Buffy", :age 28, :name "Glory"}
 {:nemesis "Whales", :age 27, :name "Jonah"}
 {:nemesis "Spiders", :age 27, :name "Jonah"})

Common Lisp

(defparameter *table-A* '((27 "Jonah") (18 "Alan") (28 "Glory") (18 "Popeye") (28 "Alan")))

(defparameter *table-B* '(("Jonah" "Whales") ("Jonah" "Spiders") ("Alan" "Ghosts") ("Alan" "Zombies") ("Glory" "Buffy")))

;; Hash phase
(defparameter *hash-table* (make-hash-table :test #'equal))

(loop for (i r) in *table-A*
   for value = (gethash r *hash-table* (list nil))  do
   (setf (gethash r *hash-table*) value)
   (push (list i r) (first value)))

;; Join phase
(loop for (i r) in *table-B* do
     (let ((val (car (gethash i *hash-table*))))
       (loop for (a b) in val do
	    (format t "{~a ~a} {~a ~a}~%"  a b i r))))


{27 Jonah} {Jonah Whales}
{27 Jonah} {Jonah Spiders}
{28 Alan} {Alan Ghosts}
{18 Alan} {Alan Ghosts}
{28 Alan} {Alan Zombies}
{18 Alan} {Alan Zombies}
{28 Glory} {Glory Buffy}

D

import std.stdio, std.typecons;

auto hashJoin(size_t index1, size_t index2, T1, T2)
             (in T1[] table1, in T2[] table2) pure /*nothrow*/ @safe
if (is(typeof(T1.init[index1]) == typeof(T2.init[index2]))) {
    // Hash phase.
    T1[][typeof(T1.init[index1])] h;
    foreach (const s; table1)
        h[s[index1]] ~= s;

    // Join phase.
    Tuple!(const T1, const T2)[] result;
    foreach (const r; table2)
        foreach (const s; h.get(r[index2], null)) // Not nothrow.
            result ~= tuple(s, r);

    return result;
}

void main() {
    alias T = tuple;
    immutable table1 = [T(27, "Jonah"),
                        T(18, "Alan"),
                        T(28, "Glory"),
                        T(18, "Popeye"),
                        T(28, "Alan")];
    immutable table2 = [T("Jonah", "Whales"),
                        T("Jonah", "Spiders"),
                        T("Alan",  "Ghosts"),
                        T("Alan",  "Zombies"),
                        T("Glory", "Buffy")];

    foreach (const row; hashJoin!(1, 0)(table1, table2))
        writefln("(%s, %5s) (%5s, %7s)", row[0][], row[1][]);
}

(27, Jonah) (Jonah,  Whales)
(27, Jonah) (Jonah, Spiders)
(18,  Alan) ( Alan,  Ghosts)
(28,  Alan) ( Alan,  Ghosts)
(18,  Alan) ( Alan, Zombies)
(28,  Alan) ( Alan, Zombies)
(28, Glory) (Glory,   Buffy)

=={{header|Déjà Vu}}== {{trans|Python}}

hashJoin table1 index1 table2 index2:
    local :h {}
    # hash phase
    for s in table1:
        local :key s! index1
        if not has h key:
            set-to h key []
        push-to h! key s
    # join phase
    []
    for r in table2:
        for s in copy h! r! index2:
            push-through swap [ s r ]

local :table1 [ [ 27 "Jonah" ] [ 18 "Alan" ] [ 28 "Glory" ] [ 18 "Popeye" ] [ 28 "Alan" ] ]
local :table2 [ [ "Jonah" "Whales" ] [ "Jonah" "Spiders" ] [ "Alan" "Ghosts" ] [ "Alan" "Zombies" ] [ "Glory" "Buffy" ] ]

for row in hashJoin table1 1 table2 0:
    !. row

[ [ 27 "Jonah" ] [ "Jonah" "Whales" ] ]
[ [ 27 "Jonah" ] [ "Jonah" "Spiders" ] ]
[ [ 28 "Alan" ] [ "Alan" "Ghosts" ] ]
[ [ 18 "Alan" ] [ "Alan" "Ghosts" ] ]
[ [ 28 "Alan" ] [ "Alan" "Zombies" ] ]
[ [ 18 "Alan" ] [ "Alan" "Zombies" ] ]
[ [ 28 "Glory" ] [ "Glory" "Buffy" ] ]

EchoLisp

Since this is a real, professional application, we build the hash tables in permanent (local) storage.


(define ages '((27 "Jonah") (18 "Alan") (28 "Glory") (18 "Popeye") (28 "Alan")))
(define nemesis '(("Jonah" "Whales") ("Jonah" "Spiders") ("Alan" "Ghosts") ("Alan" "Zombies") ("Glory" "Buffy")))

;; table: table name
;; source : input list
;; key-proc : procedure returning the join value ('name' in this task)

(define (table-hash table source key-proc )
(local-make-store table)
(for ((r source))
	(local-put-value
		(key-proc r)
		(append (list r) (local-get-value (key-proc r) table)) table)))

;; build the two tables
(define-syntax-rule (second record) (cadr record))
(define (key-name-age record) (second record))
(table-hash 'AGES ages key-name-age)

(define (key-nemesis-name record) (first record))
(table-hash 'NEMESIS nemesis key-nemesis-name)

;; join
(for* ((k (local-keys 'AGES))
	  (a (local-get-value k 'AGES))
	  (n (local-get-value k 'NEMESIS)))
	  (writeln a n))


(28 "Alan")     ("Alan" "Zombies")
(28 "Alan")     ("Alan" "Ghosts")
(18 "Alan")     ("Alan" "Zombies")
(18 "Alan")     ("Alan" "Ghosts")
(28 "Glory")     ("Glory" "Buffy")
(27 "Jonah")     ("Jonah" "Spiders")
(27 "Jonah")     ("Jonah" "Whales")

ECL


LeftRec := RECORD
  UNSIGNED1 Age;
  STRING6   Name;
END;

LeftFile := DATASET([{27,'Jonah'},{18,'Alan'},{28,'Glory'},{18,'Popeye'},{28,'Alan'}],LeftRec);

RightRec := RECORD
  STRING6   Name;
  STRING7   Nemesis;
END;

RightFile := DATASET([{'Jonah','Whales'},{'Jonah','Spiders'},{'Alan','Ghosts'},{'Alan','Zombies'},{'Glory','Buffy'}],
                     RightRec);

HashJoin := JOIN(LeftFile,RightFile,Left.Name = RIGHT.Name,HASH);

HashJoin;


//The HASH JOIN is built-in to the ECL JOIN by using the HASH JOIN Flag

/*
OUTPUT:
Age Name  Nemesis
18  Alan  Ghosts
18  Alan  Zombies
28  Alan  Ghosts
28  Alan  Zombies
28  Glory Buffy
27  Jonah Whales
27  Jonah Spiders
*/

Elixir

defmodule Hash do
  def join(table1, index1, table2, index2) do
    h = Enum.group_by(table1, fn s -> elem(s, index1) end)
    Enum.flat_map(table2, fn r ->
      Enum.map(h[elem(r, index2)], fn s -> {s, r} end)
    end)
  end
end

table1 = [{27, "Jonah"},
          {18, "Alan"},
          {28, "Glory"},
          {18, "Popeye"},
          {28, "Alan"}]
table2 = [{"Jonah", "Whales"},
          {"Jonah", "Spiders"},
          {"Alan",  "Ghosts"},
          {"Alan",  "Zombies"},
          {"Glory", "Buffy"}]
Hash.join(table1, 1, table2, 0) |> Enum.each(&IO.inspect &1)


{{27, "Jonah"}, {"Jonah", "Whales"}}
{{27, "Jonah"}, {"Jonah", "Spiders"}}
{{28, "Alan"}, {"Alan", "Ghosts"}}
{{18, "Alan"}, {"Alan", "Ghosts"}}
{{28, "Alan"}, {"Alan", "Zombies"}}
{{18, "Alan"}, {"Alan", "Zombies"}}
{{28, "Glory"}, {"Glory", "Buffy"}}

Erlang


-module( hash_join ).

-export( [task/0] ).

task() ->
    Table_1 = [{27, "Jonah"}, {18, "Alan"}, {28, "Glory"}, {18, "Popeye"}, {28, "Alan"}],
    Table_2 = [{"Jonah", "Whales"}, {"Jonah", "Spiders"}, {"Alan", "Ghosts"}, {"Alan", "Zombies"}, {"Glory", "Buffy"}],
    Dict = lists:foldl( fun dict_append/2, dict:new(), Table_1 ),
    lists:flatten( [dict_find( X, Dict ) || X <- Table_2] ).


dict_append( {Key, Value}, Acc ) -> dict:append( Value, {Key, Value}, Acc ).

dict_find( {Key, Value}, Dict ) -> dict_find( dict:find(Key, Dict), Key, Value ).

dict_find( error, _Key, _Value ) -> [];
dict_find( {ok,	Values}, Key, Value ) -> [{X, {Key, Value}} || X <- Values].


15> hash_join:task().
[{{27,"Jonah"},{"Jonah","Whales"}},
 {{27,"Jonah"},{"Jonah","Spiders"}},
 {{18,"Alan"},{"Alan","Ghosts"}},
 {{28,"Alan"},{"Alan","Ghosts"}},
 {{18,"Alan"},{"Alan","Zombies"}},
 {{28,"Alan"},{"Alan","Zombies"}},
 {{28,"Glory"},{"Glory","Buffy"}}]

=={{header|F_Sharp|F#}}==

]
let main argv =
    let table1 = [27, "Jonah";
                18, "Alan";
                28, "Glory";
                18, "Popeye";
                28, "Alan"]
    let table2 = ["Jonah", "Whales";
                "Jonah", "Spiders";
                "Alan", "Ghosts";
                "Alan", "Zombies";
                "Glory", "Buffy"]
    let hash = Seq.groupBy (fun r -> snd r) table1
    table2
    |> Seq.collect (fun r ->
        hash
        |> Seq.collect (fun kv ->
            if (fst r) <> (fst kv) then []
            else (Seq.map (fun x -> (x, r)) (snd kv)) |> Seq.toList)
        )
    |> Seq.toList
    |> printfn "%A"
    0

[((27, "Jonah"), ("Jonah", "Whales")); ((27, "Jonah"), ("Jonah", "Spiders"));
 ((18, "Alan"), ("Alan", "Ghosts")); ((28, "Alan"), ("Alan", "Ghosts"));
 ((18, "Alan"), ("Alan", "Zombies")); ((28, "Alan"), ("Alan", "Zombies"));
 ((28, "Glory"), ("Glory", "Buffy"))]

Forth

{{works with|Forth}} Works with any ANS Forth

Needs the FMS-SI (single inheritance) library code located here: http://soton.mpeforth.com/flag/fms/index.html


include FMS-SI.f
include FMS-SILib.f

\ Since the same join attribute, Name, occurs more than once
\ in both tables for this problem we need a hash table that
\ will accept and retrieve multiple identical keys if we want
\ an efficient solution for large tables. We make use
\ of the hash collision handling feature of class hash-table.

\ Subclass hash-table-m allows multiple entries with the same key.
\ After a get: hit one can inspect for additional entries with
\ the same key by using next: until false is returned.

:class hash-table-m <super hash-table

\ called within insert: method in superclass
 :m (do-search): ( node hash -- idx hash false )
      swap drop idx @ swap false ;m
 :m next: ( -- val true | false )
    last-node @ dup
    if
      begin
       ( node ) next: dup
      while
        dup key@: @: key-addr @ key-len @ compare 0=
             if dup last-node ! val@: true exit then
      repeat
    then ;m
;class

\ begin hash phase
: obj ( addr len -- obj )
  heap> string+ dup >r !: r> ;

hash-table-m R   1 r init
s" Whales "   obj s" Jonah" r insert:
s" Spiders "  obj s" Jonah" r insert:
s" Ghosts "   obj s" Alan"  r insert:
s" Buffy "    obj s" Glory" r insert:
s" Zombies "  obj s" Alan"  r insert:
s" Vampires " obj s" Jonah" r insert:
\ end hash phase

\ create Age Name table S
o{ o{ 27 'Jonah' }
   o{ 18 'Alan' }
   o{ 28 'Glory' }
   o{ 18 'Popeye' }
   o{ 28 'Alan' } } value s

\ Q is a place to store the relation
object-list2 Q

\ join phase
: join \ { obj | list -- }
  0 locals| list obj |
  1 obj at: @: r get: \ hash the join-attribute and search table r
  if \ we have a match, so concatenate and save in q
    heap> object-list2 to list list q add: \ start a new sub-list in q
    0 obj at: copy: list add: \ place age from list s in q
    1 obj at: copy: list add: \ place join-attribute (name) from list s in q
    ( str-obj ) copy: list add: \ place first nemesis in q
    begin
      r next: \ check for more nemeses
    while
       ( str-obj ) copy: list add: \ place next nemesis in q
    repeat
  then ;

: probe
  begin
    s each: \ for each tuple object in s
  while
    ( obj ) join \ pass the object to function join
  repeat ;

probe \ execute the probe function

q p: \ print the saved relation

\ free allocated memory
s <free
r free2:
q free:


o{
o{ 27 'Jonah' Whales Spiders Vampires }
o{ 18 'Alan' Ghosts Zombies }
o{ 28 'Glory' Buffy }
o{ 28 'Alan' Ghosts Zombies } }

Go

package main

import "fmt"

func main() {
    tableA := []struct {
        value int
        key   string
    }{
        {27, "Jonah"}, {18, "Alan"}, {28, "Glory"}, {18, "Popeye"},
        {28, "Alan"},
    }
    tableB := []struct {
        key   string
        value string
    }{
        {"Jonah", "Whales"}, {"Jonah", "Spiders"},
        {"Alan", "Ghosts"}, {"Alan", "Zombies"}, {"Glory", "Buffy"},
    }
    // hash phase
    h := map[string][]int{}
    for i, r := range tableA {
        h[r.key] = append(h[r.key], i)
    }
    // join phase
    for _, x := range tableB {
        for _, a := range h[x.key] {
            fmt.Println(tableA[a], x)
        }
    }
}


{27 Jonah} {Jonah Whales}
{27 Jonah} {Jonah Spiders}
{18 Alan} {Alan Ghosts}
{28 Alan} {Alan Ghosts}
{18 Alan} {Alan Zombies}
{28 Alan} {Alan Zombies}
{28 Glory} {Glory Buffy}

Groovy

Semi-imperative style:


def hashJoin(table1, col1, table2, col2) {

    def hashed = table1.groupBy { s -> s[col1] }

    def q = [] as Set

    table2.each { r ->
        def join = hashed[r[col2]]
        join.each { s ->
            q << s.plus(r)
        }
    }

    q
}

More functional style:


def hashJoin(table1, col1, table2, col2) {

    def hashed = table1.groupBy { s -> s[col1] }

    table2.collect { r ->
        hashed[r[col2]].collect { s -> s.plus(r) }
    }.flatten()
}

Sample run (either version as the result is the same):


def s = [[age: 27, name: 'Jonah'],
         [age: 18, name: 'Alan'],
         [age: 28, name: 'Glory'],
         [age: 18, name: 'Popeye'],
         [age: 28, name: 'Alan']]

def r = [[name: 'Jonah', nemesis: 'Whales'],
         [name: 'Jonah', nemesis: 'Spiders'],
         [name: 'Alan', nemesis: 'Ghosts'],
         [name: 'Alan', nemesis: 'Zombies'],
         [name: 'Glory', nemesis: 'Buffy']]

hashJoin(s, "name", r, "name").sort {it.name}.each { println it }

produces:


[age:18, name:Alan, nemesis:Ghosts]
[age:28, name:Alan, nemesis:Ghosts]
[age:18, name:Alan, nemesis:Zombies]
[age:28, name:Alan, nemesis:Zombies]
[age:28, name:Glory, nemesis:Buffy]
[age:27, name:Jonah, nemesis:Whales]
[age:27, name:Jonah, nemesis:Spiders]

Haskell

The ST monad allows us to utilise mutable memory behind a referentially transparent interface, allowing us to use hashtables (efficiently).

Our hashJoin function takes two lists and two selector functions.

Placing all relations with the same selector value in a list in the hashtable allows us to join many to one/many relations.

{-# LANGUAGE LambdaCase, TupleSections #-}
import qualified Data.HashTable.ST.Basic as H
import Data.Hashable
import Control.Monad.ST
import Control.Monad
import Data.STRef

hashJoin :: (Eq k, Hashable k) =>
            [t] -> (t -> k) -> [a] -> (a -> k) -> [(t, a)]
hashJoin xs fx ys fy = runST $ do
  l <- newSTRef []
  ht <- H.new
  forM_ ys $ \y -> H.insert ht (fy y) =<<
    (H.lookup ht (fy y) >>= \case
      Nothing -> return [y]
      Just v -> return (y:v))
  forM_ xs $ \x -> do
    H.lookup ht (fx x) >>= \case
      Nothing -> return ()
      Just v -> modifySTRef' l ((map (x,)  v) ++)
  readSTRef l

main = mapM_ print $ hashJoin
    [(1, "Jonah"), (2, "Alan"), (3, "Glory"), (4, "Popeye")]
        snd
    [("Jonah", "Whales"), ("Jonah", "Spiders"),
      ("Alan", "Ghosts"), ("Alan", "Zombies"), ("Glory", "Buffy")]
        fst


((3,"Glory"),("Glory","Buffy"))
((2,"Alan"),("Alan","Zombies"))
((2,"Alan"),("Alan","Ghosts"))
((1,"Jonah"),("Jonah","Spiders"))
((1,"Jonah"),("Jonah","Whales"))

The task require hashtables; however, a cleaner and more functional solution would be to use Data.Map (based on binary trees):

{-# LANGUAGE TupleSections #-}
import qualified Data.Map as M
import Data.List
import Data.Maybe
import Control.Applicative

mapJoin xs fx ys fy = joined
  where yMap = foldl' f M.empty ys
        f m y = M.insertWith (++) (fy y) [y] m
        joined = concat .
                 mapMaybe (\x -> map (x,) <$> M.lookup (fx x) yMap) $ xs

main = mapM_ print $ mapJoin
    [(1, "Jonah"), (2, "Alan"), (3, "Glory"), (4, "Popeye")]
        snd
    [("Jonah", "Whales"), ("Jonah", "Spiders"),
     ("Alan", "Ghosts"), ("Alan", "Zombies"), ("Glory", "Buffy")]
        fst


((1,"Jonah"),("Jonah","Spiders"))
((1,"Jonah"),("Jonah","Whales"))
((2,"Alan"),("Alan","Zombies"))
((2,"Alan"),("Alan","Ghosts"))
((3,"Glory"),("Glory","Buffy"))

J

Data:

table1=: ;:;._2(0 :0)
  27 Jonah
  18 Alan
  28 Glory
  18 Popeye
  28 Alan
)

table2=: ;:;._2(0 :0)
  Jonah Whales
  Jonah Spiders
  Alan Ghosts
  Alan Zombies
  Glory Buffy
)

The task does not specify the hash function to use, so we'll use an identity function. But [[SHA-1]] could be used instead, with a little more work (you'd need to convert the name into the bit vector needed by the SHA-1 interface). Practically speaking, though, the only benefit of SHA-1 in this context would be to slow down the join.

Implementation:

hash=: ]
dojoin=:3 :0
  c1=. {.{.y
  c2=. (1 {"1 y) -. a:
  c3=. (2 {"1 y) -. a:
  >{c1;c2;<c3
)

JOIN=: ; -.&a: ,/each(hash@{."1 <@dojoin/. ]) (1 1 0&#inv@|."1 table1), 1 0 1#inv"1 table2

Result:

   JOIN
┌─────┬──┬───────┐
│Jonah│27│Whales │
├─────┼──┼───────┤
│Jonah│27│Spiders│
├─────┼──┼───────┤
│Alan │18│Ghosts │
├─────┼──┼───────┤
│Alan │18│Zombies│
├─────┼──┼───────┤
│Alan │28│Ghosts │
├─────┼──┼───────┤
│Alan │28│Zombies│
├─────┼──┼───────┤
│Glory│28│Buffy  │
└─────┴──┴───────┘

Java

import java.util.*;

public class HashJoin {

    public static void main(String[] args) {
        String[][] table1 = {{"27", "Jonah"}, {"18", "Alan"}, {"28", "Glory"},
        {"18", "Popeye"}, {"28", "Alan"}};

        String[][] table2 = {{"Jonah", "Whales"}, {"Jonah", "Spiders"},
        {"Alan", "Ghosts"}, {"Alan", "Zombies"}, {"Glory", "Buffy"},
        {"Bob", "foo"}};

        hashJoin(table1, 1, table2, 0).stream()
                .forEach(r -> System.out.println(Arrays.deepToString(r)));
    }

    static List<String[][]> hashJoin(String[][] records1, int idx1,
            String[][] records2, int idx2) {

        List<String[][]> result = new ArrayList<>();
        Map<String, List<String[]>> map = new HashMap<>();

        for (String[] record : records1) {
            List<String[]> v = map.getOrDefault(record[idx1], new ArrayList<>());
            v.add(record);
            map.put(record[idx1], v);
        }

        for (String[] record : records2) {
            List<String[]> lst = map.get(record[idx2]);
            if (lst != null) {
                lst.stream().forEach(r -> {
                    result.add(new String[][]{r, record});
                });
            }
        }

        return result;
    }
}

[[27, Jonah], [Jonah, Whales]]
[[27, Jonah], [Jonah, Spiders]]
[[18, Alan], [Alan, Ghosts]]
[[28, Alan], [Alan, Ghosts]]
[[18, Alan], [Alan, Zombies]]
[[28, Alan], [Alan, Zombies]]
[[28, Glory], [Glory, Buffy]]

JavaScript

ES6

(() => {
    'use strict';

    // hashJoin :: [Dict] -> [Dict] -> String -> [Dict]
    let hashJoin = (tblA, tblB, strJoin) => {

        let [jA, jB] = strJoin.split('='),
            M = tblB.reduce((a, x) => {
                let id = x[jB];
                return (
                    a[id] ? a[id].push(x) : a[id] = [x],
                    a
                );
            }, {});

        return tblA.reduce((a, x) => {
            let match = M[x[jA]];
            return match ? (
                a.concat(match.map(row => dictConcat(x, row)))
            ) : a;
        }, []);
    },

    // dictConcat :: Dict -> Dict -> Dict
    dictConcat = (dctA, dctB) => {
        let ok = Object.keys;
        return ok(dctB).reduce(
            (a, k) => (a['B_' + k] = dctB[k]) && a,
            ok(dctA).reduce(
                (a, k) => (a['A_' + k] = dctA[k]) && a, {}
            )
        );
    };


    // TEST
    let lstA = [
        { age: 27, name: 'Jonah' },
        { age: 18, name: 'Alan' },
        { age: 28, name: 'Glory' },
        { age: 18, name: 'Popeye' },
        { age: 28, name: 'Alan' }
    ],
    lstB = [
        { character: 'Jonah', nemesis: 'Whales' },
        { character: 'Jonah', nemesis: 'Spiders' },
        { character: 'Alan', nemesis: 'Ghosts' },
        { character:'Alan', nemesis: 'Zombies' },
        { character: 'Glory', nemesis: 'Buffy' },
        { character: 'Bob', nemesis: 'foo' }
    ];

    return hashJoin(lstA, lstB, 'name=character');

})();

[{"A_age":27,"A_name":"Jonah","B_character":"Jonah","B_nemesis":"Whales"},
{"A_age":27,"A_name":"Jonah","B_character":"Jonah","B_nemesis":"Spiders"},
{"A_age":18,"A_name":"Alan","B_character":"Alan","B_nemesis":"Ghosts"},
{"A_age":18,"A_name":"Alan","B_character":"Alan","B_nemesis":"Zombies"},
{"A_age":28,"A_name":"Glory","B_character":"Glory","B_nemesis":"Buffy"},
{"A_age":28,"A_name":"Alan","B_character":"Alan","B_nemesis":"Ghosts"},
{"A_age":28,"A_name":"Alan","B_character":"Alan","B_nemesis":"Zombies"}]

jq

Relational tables can be represented in several ways in JSON, and so in this section we present two distinct "hash join" functions in jq:

"hashJoin" can be used if the tables are represented as arrays of JSON objects, or as arrays of arrays, but the result may include the join-column twice;
"hashJoinArrays" is intended for use if the tables are represented as arrays of arrays, and avoids the duplication mentioned above.

Both versions are relationally symmetric, and both versions allow the join columns to contain any JSON value. To achieve this generality, the collision-free hash function, h, is used.

hashJoin

# hashJoin(table1; key1; table2; key2) expects the two tables to be
# arrays, either of JSON objects, or of arrays.

# In the first case, that is, if the table's rows are represented as
# objects, then key1 should be the key of the join column of table1,
# and similarly for key2; if the join columns have different names,
# then they will both be included in the resultant objects.

# In the second case, that is, if the rows are arrays, then the
# 0-based indices of the join columns should be specified, and the
# rows are simply pasted together, resulting in duplication of the
# join columns.
#
def hashJoin(table1; key1; table2; key2):
  # collision-free hash function:
  def h:
    if type == "object" then with_entries(.value = (.value|h)) | tostring
    elif type == "array" then map(h)|tostring
    else (type[0:1]+tostring)
    end;

  # hash phase:
  reduce table1[] as $row
    ({};
     ($row[key1]|h) as $key
     | . + { ($key): (.[$key] + [$row]) } )
  | . as $hash
  # join phase
  | reduce table2[] as $row
      ([];
       ($row[key2]|h) as $key
       | if $hash|has($key) then
           reduce $hash[$key][] as $r (.; . +  [ $row + $r ] )
  	 else . end)
;

'''Example'''

def table1:
  [ {"age": 27, "name": "Jonah"},
    {"age": 18, "name": "Alan"},
    {"age": 28, "name": "Glory"},
    {"age": 18, "name": "Popeye"},
    {"age": 28, "name": "Alan"} ]
;

def table2:
  [ {"name": "Jonah", "nemesis": "Whales"},
    {"name": "Jonah", "nemesis": "Spiders"},
    {"name": "Alan", "nemesis": "Ghosts"},
    {"name": "Alan", "nemesis": "Zombies"},
    {"name": "Glory", "nemesis": "Buffy"} ]
;

def table1a:
  [[27, "Jonah"],
   [18, "Alan"],
   [28, "Glory"],
   [18, "Popeye"],
   [28, "Alan"] ]
;

def table2a:
  [["Jonah", "Whales"],
   ["Jonah", "Spiders"],
   ["Alan", "Ghosts"],
   ["Alan", "Zombies"],
   ["Glory", "Buffy"],
   ["Holmes", "Moriarty"] ]
;

def pp:
  reduce .[] as $row (""; . + "\n" + ($row|tostring));

( hashJoin(table1; "name"; table2; "name"),
  hashJoin(table1a; 1; table2a; 0)
) | pp

$ jq -c -r -n -f HashJoin.jq

{"age":27,"name":"Jonah","nemesis":"Whales"}
{"age":27,"name":"Jonah","nemesis":"Spiders"}
{"age":28,"name":"Alan","nemesis":"Ghosts"}
{"age":28,"name":"Alan","nemesis":"Zombies"}
{"age":28,"name":"Glory","nemesis":"Buffy"}

[27,"Jonah","Jonah","Whales"]
[27,"Jonah","Jonah","Spiders"]
[28,"Alan","Alan","Ghosts"]
[28,"Alan","Alan","Zombies"]
[28,"Glory","Glory","Buffy"]

hashJoinArrays

# The tables should be arrays of arrays;
# index1 and index2 should be the 0-based indices of the join columns.
#
def hashJoinArrays(table1; index1; table2; index2):
  # collision-free hash function:
  def h:
    if type == "object" then with_entries(.value = (.value|h)) | tostring
    elif type == "array" then map(h)|tostring
    else (type[0:1]+tostring)
    end;

  # hash phase:
  reduce table1[] as $row
    ({};
     ($row[index1]|h) as $key
     | . + (.[$key] += [ $row ])  )
  | . as $hash
  # join phase
  | reduce table2[] as $row
      ([];
       ($row[index2]|h) as $key
       | if $hash|has($key) then
           reduce $hash[$key][] as $r
	     (.;
	      . + [ $r + $row[0:index2] + $row[index2+1:] ] )
  	 else . end)
;

'''Example'''

In the following example, the previously defined pretty-print function (pp) and tables (table1 and table2) are used, so their definitions are not repeated here.

hashJoinArrays(table1; 1; table2; 0) | pp

$ jq -c -r -n -f HashJoinArrays.jq

[27,"Jonah","Whales"]
[27,"Jonah","Spiders"]
[28,"Alan","Ghosts"]
[28,"Alan","Zombies"]
[28,"Glory","Buffy"]

Julia

{{works with|Julia|0.6}} For dataframes there is a builtin function join:

using DataFrames

A = DataFrame(Age = [27, 18, 28, 18, 28], Name = ["Jonah", "Alan", "Glory", "Popeye", "Alan"])
B = DataFrame(Name = ["Jonah", "Jonah", "Alan", "Alan", "Glory"],
    Nemesis = ["Whales", "Spiders", "Ghosts", "Zombies", "Buffy"])
AB = join(A, B, on = :Name)

@show A B AB

A = 5×2 DataFrames.DataFrame
│ Row │ Age │ Name     │
├─────┼─────┼──────────┤
│ 1   │ 27  │ "Jonah"  │
│ 2   │ 18  │ "Alan"   │
│ 3   │ 28  │ "Glory"  │
│ 4   │ 18  │ "Popeye" │
│ 5   │ 28  │ "Alan"   │
B = 5×2 DataFrames.DataFrame
│ Row │ Name    │ Nemesis   │
├─────┼─────────┼───────────┤
│ 1   │ "Jonah" │ "Whales"  │
│ 2   │ "Jonah" │ "Spiders" │
│ 3   │ "Alan"  │ "Ghosts"  │
│ 4   │ "Alan"  │ "Zombies" │
│ 5   │ "Glory" │ "Buffy"   │
AB = 7×3 DataFrames.DataFrame
│ Row │ Age │ Name    │ Nemesis   │
├─────┼─────┼─────────┼───────────┤
│ 1   │ 18  │ "Alan"  │ "Ghosts"  │
│ 2   │ 18  │ "Alan"  │ "Zombies" │
│ 3   │ 28  │ "Alan"  │ "Ghosts"  │
│ 4   │ 28  │ "Alan"  │ "Zombies" │
│ 5   │ 28  │ "Glory" │ "Buffy"   │
│ 6   │ 27  │ "Jonah" │ "Whales"  │
│ 7   │ 27  │ "Jonah" │ "Spiders" │

Following the task hint:

function hashjoin(A::Array, ja::Int, B::Array, jb::Int)
    M = Dict(t[jb] => filter(l -> l[jb] == t[jb], B) for t in B)
    return collect([a, b] for a in A for b in get(M, a[ja], ()))
end

table1 = [(27, "Jonah"),
          (18, "Alan"),
          (28, "Glory"),
          (18, "Popeye"),
          (28, "Alan")]
table2 = [("Jonah", "Whales"),
          ("Jonah", "Spiders"),
          ("Alan", "Ghosts"),
          ("Alan", "Zombies"),
          ("Glory", "Buffy")]

for r in hashjoin(table1, 2, table2, 1)
    println(r)
end

Tuple{Any,String}[(27, "Jonah"), ("Jonah", "Whales")]
Tuple{Any,String}[(27, "Jonah"), ("Jonah", "Spiders")]
Tuple{Any,String}[(18, "Alan"), ("Alan", "Ghosts")]
Tuple{Any,String}[(18, "Alan"), ("Alan", "Zombies")]
Tuple{Any,String}[(28, "Glory"), ("Glory", "Buffy")]
Tuple{Any,String}[(28, "Alan"), ("Alan", "Ghosts")]
Tuple{Any,String}[(28, "Alan"), ("Alan", "Zombies")]

Kotlin

data class A(val age: Int, val name: String)

data class B(val character: String, val nemesis: String)

data class C(val rowA: A, val rowB: B)

fun hashJoin(tableA: List<A>, tableB: List<B>): List<C> {
    val mm = tableB.groupBy { it.character }
    val tableC = mutableListOf<C>()
    for (a in tableA) {
        val value = mm[a.name] ?: continue
        for (b in value) tableC.add(C(a, b))
    }
    return tableC.toList()
}

fun main(args: Array<String>) {
    val tableA = listOf(
        A(27, "Jonah"),
        A(18, "Alan"),
        A(28, "Glory"),
        A(18, "Popeye"),
        A(28, "Alan")
    )
    val tableB = listOf(
        B("Jonah", "Whales"),
        B("Jonah", "Spiders"),
        B("Alan", "Ghosts"),
        B("Alan", "Zombies"),
        B("Glory", "Buffy")
    )
    val tableC = hashJoin(tableA, tableB)
    println("A.Age A.Name B.Character B.Nemesis")
    println("----- ------ ----------- ---------")
    for (c in tableC) {
        print("${c.rowA.age}    ${c.rowA.name.padEnd(6)} ")
        println("${c.rowB.character.padEnd(6)}      ${c.rowB.nemesis}")
    }
}


A.Age A.Name B.Character B.Nemesis
----- ------ ----------- ---------
27    Jonah  Jonah       Whales
27    Jonah  Jonah       Spiders
18    Alan   Alan        Ghosts
18    Alan   Alan        Zombies
28    Glory  Glory       Buffy
28    Alan   Alan        Ghosts
28    Alan   Alan        Zombies

LFE


(defun hash (column table)
  (lists:foldl
    (lambda (x acc)
      (orddict:append (proplists:get_value column x) x acc))
    '()
    table))

(defun get-hash (col hash-table)
  (proplists:get_value
     (proplists:get_value col r)
     hashed))

(defun merge (row-1 row-2)
  (orddict:merge
    (lambda (k v1 v2) v2)
    (lists:sort row-1)
    (lists:sort row-2)))

(defun hash-join (table-1 col-1 table-2 col-2)
  (let ((hashed (hash col-1 table-1)))
    (lc ((<- r table-2))
        (lc ((<- s (get-hash col-2 hashed)))
            (merge r s)))))

Table definitions in the LFE REPL:


> (set ss '((#(age 27) #(name "Jonah"))
            (#(age 18) #(name "Alan"))
            (#(age 28) #(name "Glory"))
            (#(age 18) #(name "Popeye"))
            (#(age 28) #(name "Alan"))))

> (set rs '((#(nemesis "Whales") #(name "Jonah"))
            (#(nemesis "Spiders") #(name "Jonah"))
            (#(nemesis "Ghosts") #(name "Alan"))
            (#(nemesis "Zombies") #(name "Alan"))
            (#(nemesis "Buffy") #(name "Glory"))))

Output in LFE REPL:


> (hash-join ss 'name rs 'name)
(((#(age 27) #(name "Jonah") #(nemesis "Whales")))
 ((#(age 27) #(name "Jonah") #(nemesis "Spiders")))
 ((#(age 18) #(name "Alan") #(nemesis "Ghosts"))
  (#(age 28) #(name "Alan") #(nemesis "Ghosts")))
 ((#(age 18) #(name "Alan") #(nemesis "Zombies"))
  (#(age 28) #(name "Alan") #(nemesis "Zombies")))
 ((#(age 28) #(name "Glory") #(nemesis "Buffy"))))

M2000 Interpreter


Module HashJoin {
      \\ normally we define variables when we put values to names
      \\ so we can remove these two lines
      Def Name$, Nemesis$
      Def Long m, mc, items_size, A

      \\ Lets make a container which use keys with hash function
      Inventory A
      \\ A now is a pointer to an Inventory, with Len(A)=0
      \\ Print Type$(A)="Inventory"

      \\ empty stack. We use current stack to place data
      Flush
      \Input B
      data "Jonah", "Whales"
      data "Jonah", "Spiders"
      data "Alan", "Ghosts"
      data "Alan", "Zombies"
      data "Glory", "Buffy"
      \\ Keys are unique, This is the HASH PHASE
      While not empty {
            Read Name$, Nemesis$
            If Exist(A, Name$) Then {
                  m=Eval(A)  ' get a pointer to array
                  Stack m {Data Nemesis$}
            } Else Append A, Name$:=Stack:=Nemesis$  ' a stack object with one item
      }
      \\ Input A, this is the Long Table
      data 27, "Jonah"
      data 18, "Alan"
      data 28, "Glory"
      data 18, "Popeye"
      data 28, "Alan"

      \\ This is the JOIN PHASE

      items_size=stack.size/2
      \\ using items_size we can append data (using data) to stack
      \\ $(0) is the default handler for columns.
      \\ Letters justify to left, numbers to right.
      \\ Letters can use more columns, and maybe wrap to more lines.

      Print $(0), "Output during join"
      Print "A.Age", "A.Name","B.Character", "B.Nemesis"
      While items_size>0 {
            Read Age, Name$
            If exist(A, Name$) Then {
                  m=Eval(A)   ' extract a pointer, this is for a stack object
                  mc=Each(m)  ' make an iterator
                  While mc {
                        \\ we use $(1) for left justify numbers too
                        \\ normal StackItem$(stackobject) return top only
                        \\ we have to use StackItem$(stackobject, 3) to get 3rd
                        \\ or StackItem(stackobject, 3) if it is numeric.
                        \\ but here mc is iterator, and place the cursor value to it
                       Print $(1), Age, Name$,Name$, StackItem$(mc)
                        \\ so now we place at the end of current stack the same output
                       Data Age, Name$,Name$, StackItem$(mc)
                  }
            }
            items_size--
      }
      \\ split rem line after : to use second way
      rem : goto secondway
      Print $(0), "Output after join"
      Print "A.Age", "A.Name","B.Character", "B.Nemesis"
      While not Empty {
            Print $(1), Number, Letter$, Letter$, Letter$
      }
      Exit
secondway:
      Print $(0), "Output after join using format$()"
      Print Format$("{0:5} {1:10} {2:10} {3:20}","A.Age", "A.Name","B.Character", "B.Nemesis")
      While not Empty {
            Print format$("{0::5} {1:10} {2:10} {3:20}", Number, Letter$, Letter$, Letter$)
      }
}
HashJoin

27    Jonah      Jonah      Whales
27    Jonah      Jonah      Spiders
18    Alan       Alan       Ghosts
18    Alan       Alan       Zombies
28    Glory      Glory      Buffy
28    Alan       Alan       Ghosts
28    Alan       Alan       Zombies