Hash join
You are encouraged to solve this task according to the task description, using any language you may know.
An 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 nested loop join algorithm, but a more scalable alternative is the hash join algorithm.
Task[|_}}%20*%2F%20 edit]
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.
Guidance
The "hash join" algorithm consists of two steps:
- Hash phase: Create a 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 jA = the join column ID of table A
let jB = the join column ID of table B
let MB = 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 MB under key b(jB)
for each row a in table A:
for each row b in multimap MB under key a(jA):
let c = the concatenation of row a and row b
place row c in table C
Test-case
| Input | Output | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
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"]].
11l
F hash_join(table1, table2)
DefaultDict[String, [(Int, String)]] h
L(s) table1
h[s[1]].append(s)
[((Int, String), (String, String))] res
L(r) table2
L(s) h[r[0]]
res [+]= (s, r)
R res
V table1 = [(27, ‘Jonah’),
(18, ‘Alan’),
(28, ‘Glory’),
(18, ‘Popeye’),
(28, ‘Alan’)]
V table2 = [(‘Jonah’, ‘Whales’),
(‘Jonah’, ‘Spiders’),
(‘Alan’, ‘Ghosts’),
(‘Alan’, ‘Zombies’),
(‘Glory’, ‘Buffy’)]
L(row) hash_join(table1, table2)
print(row)- Output:
((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))
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
- Output:
{{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"}}
Arturo
hashJoin: function [t1, t2][
result: []
h: #[]
loop t1 's [
if not? key? h s\1 -> h\[s\1]: []
h\[s\1]: h\[s\1] ++ @[s]
]
loop t2 'r [
loop h\[r\0] 's [
'result ++ @[@[s r]]
]
]
return result
]
table1: [
[27 "Jonah"]
[18 "Alan"]
[28 "Glory"]
[18 "Popeye"]
[28 "Alan"]
]
table2: [
["Jonah" "Whales"]
["Jonah" "Spiders"]
["Alan" "Ghosts"]
["Alan" "Zombies"]
["Glory" "Buffy"]
]
loop hashJoin table1 table2 'row ->
print row
- Output:
[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]
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 "." $0
gsub(/,/,"&" p ".",tmp)
return(tmp)
}
TABLE_A input:
Age,Name 27,Jonah 18,Alan 28,Glory 18,Popeye 28,Alan
TABLE_B input:
Character,Nemesis Jonah,Whales Jonah,Spiders Alan,Ghosts Alan,Zombies Glory,Buffy
- Output:
A.Age,A.Name,B.Character,B.Nemesis 18,Alan,Alan,Ghosts 18,Alan,Alan,Zombies 28,Alan,Alan,Ghosts 28,Alan,Alan,Zombies 28,Glory,Glory,Buffy 27,Jonah,Jonah,Spiders 27,Jonah,Jonah,Whales
Bracmat
This solution creates a hash table for the smaller relation in the function join. This function takes as arguments the smallest table, the biggest table and then three pieces of code: two patterns that describe each table's field order and code that generates one row of output. These pieces of code are inserted in a fixed skeleton of code using macro substitution.
( (27.Jonah)
(18.Alan)
(28.Glory)
(18.Popeye)
(28.Alan)
: ?table-A
& (Jonah.Whales)
(Jonah.Spiders)
(Alan.Ghosts)
(Alan.Zombies)
(Glory.Buffy)
: ?table-B
& new$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#
- 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;
}
}
}
- Output:
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
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;
}
- Output:
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
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)))
- Output:
({: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))))
- Output:
{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][]);
}
- Output:
(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)
Déjà Vu
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- Output:
[ [ 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" ] ]
DuckDB
After some small changes as described in the following paragraph, DuckDB executes the SQL at #SQL elsewhere on this page normally, as shown below. We then verify that DuckDB uses a HASH_JOIN by running the EXPLAIN query.
Since DuckDB does not have type named 'number', we'll used 'decimal', and we'll use 'varchar' instaed of 'varchar2'. Here is the code, minus the hints and the reference to DUAL, and with a spelling correction.
create or replace table people (age decimal(3), name varchar(30));
insert into people (age, name)
select 27, 'Jonah' union all
select 18, 'Alan' union all
select 28, 'Glory' union all
select 18, 'Popeye' union all
select 28, 'Alan'
;
create or replace table nemeses (name varchar(30), nemesis varchar(30));
insert into nemeses (name, nemesis)
select 'Jonah', 'Whales' union all
select 'Jonah', 'Spiders' union all
select 'Alan' , 'Ghosts' union all
select 'Alan' , 'Zombies' union all
select 'Glory', 'Buffy'
;
select * from people join nemeses using(name);
explain select * from people join nemeses using(name);
- Output:
┌──────────────┬─────────┬─────────┐ │ age │ name │ nemesis │ │ decimal(3,0) │ varchar │ varchar │ ├──────────────┼─────────┼─────────┤ │ 27 │ Jonah │ Whales │ │ 27 │ Jonah │ Spiders │ │ 28 │ Alan │ Ghosts │ │ 28 │ Alan │ Zombies │ │ 28 │ Glory │ Buffy │ │ 18 │ Alan │ Ghosts │ │ 18 │ Alan │ Zombies │ └──────────────┴─────────┴─────────┘ # .... ┌─────────────┴─────────────┐ │ HASH_JOIN │ │ ──────────────────── │ │ Join Type: INNER │ │ │ │ Conditions: ├──────────────┐ │ name = name │ │ │ │ │ │ ~6 Rows │ │ └─────────────┬─────────────┘ │ ┌─────────────┴─────────────┐┌─────────────┴─────────────┐ │ SEQ_SCAN ││ SEQ_SCAN │ │ ──────────────────── ││ ──────────────────── │ │ nemeses ││ people │ │ ││ │ │ Projections: ││ Projections: │ │ name ││ name │ │ nemesis ││ age │ │ ││ │ │ ~5 Rows ││ ~5 Rows │ └───────────────────────────┘└───────────────────────────┘
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))
- Output:
(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)
- Output:
{{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].
- Output:
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"}}]
Emacs Lisp
(defun make-multi-map (rows)
(let ((multi-map nil))
(cl-loop for row in rows do
(let* ((name (car row))
(name-list (assoc name multi-map)))
(if name-list
(nconc name-list (list row))
(progn
(add-to-list 'multi-map (list name row) 't) ) ) ) )
multi-map) )
(defun join-tables (table1 table2)
(let ((multi-map (make-multi-map table2))
(result-table '()))
(cl-loop for row in table1 do
(let ((multi-rc (assoc (cdr row) multi-map)))
(when multi-rc
(cl-loop for multi-line in (cdr multi-rc) do
(add-to-list 'result-table
(list (car row) (cdr row) (car multi-line) (cdr multi-line))
't)))))
result-table))
(let ((table1 '((27 . "Jonah")
(18 . "Alan")
(28 . "Glory")
(18 . "Popeye")
(28 . "Alan")))
(table2 '(("Jonah" . "Whales")
("Jonah" . "Spiders")
("Alan" . "Ghosts")
("Alan" . "Zombies")
("Glory" . "Buffy"))))
(message "%s" (join-tables table1 table2)) )
FreeBASIC
Type Data1
value As Integer
key As String
End Type
Type Data2
key As String
value As String
End Type
Dim table1(5) As Data1
Dim table2(5) As Data2
table1(1).value = 27: table1(1).key = "Jonah"
table1(2).value = 18: table1(2).key = "Alan"
table1(3).value = 28: table1(3).key = "Glory"
table1(4).value = 18: table1(4).key = "Popeye"
table1(5).value = 28: table1(5).key = "Alan"
table2(1).key = "Jonah": table2(1).value = "Whales"
table2(2).key = "Jonah": table2(2).value = "Spiders"
table2(3).key = "Alan": table2(3).value = "Ghosts"
table2(4).key = "Alan": table2(4).value = "Zombies"
table2(5).key = "Glory": table2(5).value = "Buffy"
Print String(51, "-")
Print " Age | Name || Name | Nemesis"
Print String(51, "-")
For i As Integer = 1 To 5
For j As Integer = 1 To 5
If table1(i).key = table2(j).key Then
Print Using " ## | \ \ || \ \ | \ \"; table1(i).value; table1(i).key; table2(j).key; table2(j).value
End If
Next j
Next i
Sleep
- Output:
--------------------------------------------------- Age | Name || Name | 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
F#
[<EntryPoint>]
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
- Output:
[((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 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:
- Output:
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)
}
}
}
- Output:
{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');
})();
- Output:
[{"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- Output:
$ 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- Output:
$ jq -c -r -n -f HashJoinArrays.jq
[27,"Jonah","Whales"]
[27,"Jonah","Spiders"]
[28,"Alan","Ghosts"]
[28,"Alan","Zombies"]
[28,"Glory","Buffy"]
Julia
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
- Output:
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
- Output:
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}")
}
}
- Output:
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
Lua
Literal
Lua tables are implemented with hash keys, so this task is a bit anti-idiomatic for Lua. That is, if you knew in advance that this would be the primary operation on the data, then you'd likely (re-)structure the data to directly support it. But, to comply with the intent of the task, the data here is initially structured as an indexed (rather than hash-keyed) array, then hashed dynamically. (it's analogous to the Python solution, where a list is immediately converted to a dictionary - but could have began as a dictionary)
local function recA(age, name) return { Age=age, Name=name } end
local tabA = { recA(27,"Jonah"), recA(18,"Alan"), recA(28,"Glory"), recA(18,"Popeye"), recA(28,"Alan") }
local function recB(character, nemesis) return { Character=character, Nemesis=nemesis } end
local tabB = { recB("Jonah","Whales"), recB("Jonah","Spiders"), recB("Alan","Ghosts"), recB("Alan","Zombies"), recB("Glory","Buffy") }
local function hashjoin(taba, cola, tabb, colb)
local hash, join = {}, {}
for _,rowa in pairs(taba) do
if (not hash[rowa[cola]]) then hash[rowa[cola]] = {} end
table.insert(hash[rowa[cola]], rowa)
end
for _,rowb in pairs(tabb) do
for _,rowa in pairs(hash[rowb[colb]]) do
join[#join+1] = { A=rowa, B=rowb }
end
end
return join
end
for _,row in pairs(hashjoin(tabA, "Name", tabB, "Character")) do
print(row.A.Age, row.A.Name, row.B.Character, row.B.Nemesis)
end
- Output:
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
Idiomatic
Or, at least semi-idiomatic / more-idiomatic, per comments above under the "Literal" implementation. Here, a "hashlist" structure is defined to allow retrieval either by indexed-list style (the database "rows") or by hashed-array-of-lists style (the database "index"), where the hash is maintained upon insert so that a later "hashjoin" operation becomes just a "join" operation. (Note that storage/performance issues are minimal, at least at this scale, as both the keys and rows in the hash are merely references, not copies.)
local hashlist = {
new = function(self,key)
return setmetatable({key=key, hash={}, list={}}, {__index=self})
end,
insert = function(self,row)
self.list[#self.list+1] = row
if not self.hash[row[self.key]] then self.hash[row[self.key]]={} end
table.insert(self.hash[row[self.key]], row)
return self
end,
join = function(self,tabb)
local result = {}
for _,rowb in pairs(tabb.list) do
if (self.hash[rowb[tabb.key]]) then
for _,rowa in pairs(self.hash[rowb[tabb.key]]) do
result[#result+1] = { A=rowa, B=rowb }
end
end
end
return result
end
}
local function recA(age, name) return { Age=age, Name=name } end
tabA = hashlist:new("Name")
:insert(recA(27,"Jonah"))
:insert(recA(18,"Alan"))
:insert(recA(28,"Glory"))
:insert(recA(18,"Popeye"))
:insert(recA(28,"Alan"))
local function recB(character, nemesis) return { Character=character, Nemesis=nemesis } end
local tabB = hashlist:new("Character")
:insert(recB("Jonah","Whales"))
:insert(recB("Jonah","Spiders"))
:insert(recB("Alan","Ghosts"))
:insert(recB("Alan","Zombies"))
:insert(recB("Glory","Buffy"))
for _,row in pairs(tabA:join(tabB)) do
print(row.A.Age, row.A.Name, row.B.Character, row.B.Nemesis)
end
print("or vice versa:")
for _,row in pairs(tabB:join(tabA)) do
print(row.B.Age, row.B.Name, row.A.Character, row.A.Nemesis)
end
- Output:
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 or vice versa: 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- Output:
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
Mathematica / Wolfram Language
Updated version is now able to join wider tables by giving the index. The smaller table is hashed but this might result in different column ordering. Uses Associations introduced in Mathematica Version 10
hashJoin[table1_List,table1colindex_Integer,table2_List,table2colindex_Integer]:=Module[{h,f,t1,t2,tmp},
t1=If[table1colindex != 1,table1[[All,Prepend[Delete[Range@Length@table1[[1]],table1colindex],table1colindex]]],table1];
t2=If[table2colindex != 1, table2[[All,Prepend[Delete[Range@Length@table2[[1]],table2colindex],table2colindex]]],table2];
If[Length[t1]>Length[t2],tmp=t1;t1=t2;t2=tmp;];
h= GroupBy[t1,First];
f[{a_,b_List}]:={a,#}&/@b;
Partition[Flatten[Map[f,{#[[2;;]],h[#[[1]]]}&/@t2
]],Length[t1[[1]]]+Length[t2[[1]]]-1]
];
Sample run:
table1 = {{18, "Alan", 1}, {27, "Jonah", 2}, {28, "Alan", 3}, {28,
"Glory", 4}};
table2 = {{"Alan", "Ghosts"}, {"Alan", "Zombies"}, {"Glory",
"Buffy"}, {"Jonah", "Spiders"}, {"Jonah", "Whales"}};
table1colindex = 2;
table2colindex = 1;
hashJoin[table1, table1colindex, table2, table2colindex] // TableForm
Ghosts Alan 18 1
Ghosts Alan 28 3
Zombies Alan 18 1
Zombies Alan 28 3
Buffy Glory 28 4
Spiders Jonah 27 2
Whales Jonah 27 2
table1 = {{18, "Alan", 1}, {27, "Jonah", 2}, {28, "Alan", 3}, {28,
"Glory", 4}};
table2 = {{33, "Alan", "Ghosts"}, {34, "Alan", "Zombies"}, {35,
"Glory", "Buffy"}, {36, "Jonah", "Spiders"}, {37, "Jonah",
"Whales"}};
table1colindex = 2;
table2colindex = 2;
hashJoin[table1, table1colindex, table2, table2colindex] // TableForm
33 Ghosts Alan 18 1
33 Ghosts Alan 28 3
34 Zombies Alan 18 1
34 Zombies Alan 28 3
35 Buffy Glory 28 4
36 Spiders Jonah 27 2
37 Whales Jonah 27 2
table1 = {{19, "Zorro", 8}, {17, "Zorro", 7}, {17, "Zorro", 9}, {18,
"Alan", 1}, {27, "Jonah", 2}, {28, "Alan", 3}, {28, "Glory", 4}};
table2 = {{33, "Alan", "Ghosts"}, {34, "Alan", "Zombies"}, {35,
"Glory", "Buffy"}, {36, "Jonah", "Spiders"}, {37, "Jonah",
"Whales"}, {39, "Zorro", "Fox"}};
table1colindex = 2;
table2colindex = 2;
hashJoin[table1, table1colindex, table2, table2colindex] // TableForm
19 8 Zorro 39 Fox
17 7 Zorro 39 Fox
17 9 Zorro 39 Fox
18 1 Alan 33 Ghosts
18 1 Alan 34 Zombies
27 2 Jonah 36 Spiders
27 2 Jonah 37 Whales
28 3 Alan 33 Ghosts
28 3 Alan 34 Zombies
28 4 Glory 35 Buffy
Nim
import strformat, tables
type
Data1 = tuple[value: int; key: string]
Data2 = tuple[key: string; value: string]
proc `$`(d: Data1 | Data2): string = &"({d[0]}, {d[1]})"
iterator hashJoin(table1: openArray[Data1]; table2: openArray[Data2]): tuple[a: Data1; b: Data2] =
# Hash phase.
var h: Table[string, seq[Data1]]
for s in table1:
h.mgetOrPut(s.key, @[]).add(s)
# Join phase.
for r in table2:
for s in h[r.key]:
yield (s, r)
let table1 = [(27, "Jonah"),
(18, "Alan"),
(28, "Glory"),
(18, "Popeye"),
(28, "Alan")]
let table2 = [("Jonah", "Whales"),
("Jonah", "Spiders"),
("Alan", "Ghosts"),
("Alan", "Zombies"),
("Glory", "Buffy")]
for row in hashJoin(table1, table2):
echo row.a, " ", row.b
- Output:
(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)
Oberon-2
Works with oo2c version 2
MODULE HashJoin;
IMPORT
ADT:Dictionary,
ADT:LinkedList,
NPCT:Tools,
Object,
Object:Boxed,
Out;
TYPE
(* Some Aliases *)
Age= Boxed.LongInt;
Name= STRING;
Nemesis= STRING;
(* Generic Tuple *)
Tuple(E1: Object.Object; E2: Object.Object) = POINTER TO TupleDesc(E1,E2);
TupleDesc(E1: Object.Object; E2: Object.Object) = RECORD
(Object.ObjectDesc)
_1: E1;
_2: E2;
END;
(* Relations *)
RelationA = ARRAY 5 OF Tuple(Age,Name);
RelationB = ARRAY 5 OF Tuple(Name,Nemesis);
VAR
tableA: RelationA;
tableB: RelationB;
dict: Dictionary.Dictionary(Name,LinkedList.LinkedList(Age));
ll: LinkedList.LinkedList(Age);
PROCEDURE (t: Tuple(E1, E2)) INIT*(e1: E1; e2: E2);
BEGIN
t._1 := e1;
t._2 := e2;
END INIT;
PROCEDURE DoHashPhase(t: RelationA;VAR dict: Dictionary.Dictionary(Name,LinkedList.LinkedList(Age)));
VAR
i: INTEGER;
ll: LinkedList.LinkedList(Age);
BEGIN
i := 0;
WHILE (i < LEN(t)) & (t[i] # NIL) DO
IF (dict.HasKey(t[i]._2)) THEN
ll := dict.Get(t[i]._2);
ELSE
ll := NEW(LinkedList.LinkedList(Age));
dict.Set(t[i]._2,ll)
END;
ll.Append(t[i]._1);
INC(i)
END
END DoHashPhase;
PROCEDURE DoJoinPhase(t: RelationB; dict: Dictionary.Dictionary(Name,LinkedList.LinkedList(Age)));
VAR
i: INTEGER;
age: Age;
iterll: LinkedList.Iterator(Age);
BEGIN
FOR i := 0 TO LEN(t) - 1 DO
ll := dict.Get(t[i]._1);
iterll := ll.GetIterator(NIL);
WHILE iterll.HasNext() DO
age := iterll.Next();
Out.LongInt(age.value,4);
Out.Object(Tools.AdjustRight(t[i]._1,10));
Out.Object(Tools.AdjustRight(t[i]._2,10));Out.Ln
END
END
END DoJoinPhase;
BEGIN
(* tableA initialization *)
tableA[0] := NEW(Tuple(Age,Name),NEW(Age,27),"Jonah");
tableA[1] := NEW(Tuple(Age,Name),NEW(Age,18),"Alan");
tableA[2] := NEW(Tuple(Age,Name),NEW(Age,28),"Glory");
tableA[3] := NEW(Tuple(Age,Name),NEW(Age,18),"Popeye");
tableA[4] := NEW(Tuple(Age,Name),NEW(Age,28),"Alan");
(* tableB initialization *)
tableB[0] := NEW(Tuple(Name,Nemesis),"Jonah","Whales");
tableB[1] := NEW(Tuple(Name,Nemesis),"Jonah","Spiders");
tableB[2] := NEW(Tuple(Name,Nemesis),"Alan","Ghost");
tableB[3] := NEW(Tuple(Name,Nemesis),"Alan","Zombies");
tableB[4] := NEW(Tuple(Name,Nemesis),"Glory","Buffy");
dict := NEW(Dictionary.Dictionary(Name,LinkedList.LinkedList(Age)));
DoHashPhase(tableA,dict);
DoJoinPhase(tableB,dict);
END HashJoin.
Output:
27 Jonah Whales 27 Jonah Spiders 18 Alan Ghost 28 Alan Ghost 18 Alan Zombies 28 Alan Zombies 28 Glory Buffy
OCaml
This exploits the fact that Hashtbl implements a hash table that can store multiple values for a key, for an especially simple solution:
let hash_join table1 f1 table2 f2 =
let h = Hashtbl.create 42 in
(* hash phase *)
List.iter (fun s ->
Hashtbl.add h (f1 s) s) table1;
(* join phase *)
List.concat (List.map (fun r ->
List.map (fun s -> s, r) (Hashtbl.find_all h (f2 r))) table2)
Sample run:
# let table1 = [27, "Jonah";
18, "Alan";
28, "Glory";
18, "Popeye";
28, "Alan"];;
# let table2 = ["Jonah", "Whales";
"Jonah", "Spiders";
"Alan", "Ghosts";
"Alan", "Zombies";
"Glory", "Buffy"];;
# hash_join table1 snd table2 fst;;
- : ((int * string) * (string * string)) list =
[((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"))]
Perl
use Data::Dumper qw(Dumper);
sub hashJoin {
my ($table1, $index1, $table2, $index2) = @_;
my %h;
# hash phase
foreach my $s (@$table1) {
push @{ $h{$s->[$index1]} }, $s;
}
# join phase
map { my $r = $_;
map [$_, $r], @{ $h{$r->[$index2]} }
} @$table2;
}
@table1 = ([27, "Jonah"],
[18, "Alan"],
[28, "Glory"],
[18, "Popeye"],
[28, "Alan"]);
@table2 = (["Jonah", "Whales"],
["Jonah", "Spiders"],
["Alan", "Ghosts"],
["Alan", "Zombies"],
["Glory", "Buffy"]);
$Data::Dumper::Indent = 0;
foreach my $row (hashJoin(\@table1, 1, \@table2, 0)) {
print Dumper($row), "\n";
}
- Output:
$VAR1 = [[27,'Jonah'],['Jonah','Whales']]; $VAR1 = [[27,'Jonah'],['Jonah','Spiders']]; $VAR1 = [[18,'Alan'],['Alan','Ghosts']]; $VAR1 = [[28,'Alan'],['Alan','Ghosts']]; $VAR1 = [[18,'Alan'],['Alan','Zombies']]; $VAR1 = [[28,'Alan'],['Alan','Zombies']]; $VAR1 = [[28,'Glory'],['Glory','Buffy']];
Phix
Phix dictionary keys must be unique, but storing/extending a sequence is no trouble, and in fact simplifies the scan phase.
with javascript_semantics constant A = {{27,"Jonah"}, {18,"Alan"}, {28,"Glory"}, {18,"Popeye"}, {28,"Alan"}}, B = {{"Jonah","Whales"}, {"Jonah","Spiders"}, {"Alan", "Ghosts"}, {"Alan", "Zombies"}, {"Glory","Buffy"}}, jA = 2, jB = 1, MB = new_dict() sequence C = {} for i=1 to length(B) do object key = B[i][jB] object data = getd(key,MB) if data=0 then data = {B[i]} else data = append(data,B[i]) end if putd(key,data,MB) end for for i=1 to length(A) do object data = getd(A[i][jA],MB) if sequence(data) then for j=1 to length(data) do C = append(C,{A[i],data[j]}) end for end if end for destroy_dict(MB) pp(C,{pp_Nest,1})
- Output:
{{{27, "Jonah"}, {"Jonah", "Whales"}},
{{27, "Jonah"}, {"Jonah", "Spiders"}},
{{18, "Alan"}, {"Alan", "Ghosts"}},
{{18, "Alan"}, {"Alan", "Zombies"}},
{{28, "Glory"}, {"Glory", "Buffy"}},
{{28, "Alan"}, {"Alan", "Ghosts"}},
{{28, "Alan"}, {"Alan", "Zombies"}}}
PHP
<?php
function hashJoin($table1, $index1, $table2, $index2) {
// hash phase
foreach ($table1 as $s)
$h[$s[$index1]][] = $s;
// join phase
foreach ($table2 as $r)
foreach ($h[$r[$index2]] as $s)
$result[] = array($s, $r);
return $result;
}
$table1 = array(array(27, "Jonah"),
array(18, "Alan"),
array(28, "Glory"),
array(18, "Popeye"),
array(28, "Alan"));
$table2 = array(array("Jonah", "Whales"),
array("Jonah", "Spiders"),
array("Alan", "Ghosts"),
array("Alan", "Zombies"),
array("Glory", "Buffy"),
array("Bob", "foo"));
foreach (hashJoin($table1, 1, $table2, 0) as $row)
print_r($row);
?>
- Output:
Array
(
[0] => Array
(
[0] => 27
[1] => Jonah
)
[1] => Array
(
[0] => Jonah
[1] => Whales
)
)
Array
(
[0] => Array
(
[0] => 27
[1] => Jonah
)
[1] => Array
(
[0] => Jonah
[1] => Spiders
)
)
Array
(
[0] => Array
(
[0] => 18
[1] => Alan
)
[1] => Array
(
[0] => Alan
[1] => Ghosts
)
)
Array
(
[0] => Array
(
[0] => 28
[1] => Alan
)
[1] => Array
(
[0] => Alan
[1] => Ghosts
)
)
Array
(
[0] => Array
(
[0] => 18
[1] => Alan
)
[1] => Array
(
[0] => Alan
[1] => Zombies
)
)
Array
(
[0] => Array
(
[0] => 28
[1] => Alan
)
[1] => Array
(
[0] => Alan
[1] => Zombies
)
)
Array
(
[0] => Array
(
[0] => 28
[1] => Glory
)
[1] => Array
(
[0] => Glory
[1] => Buffy
)
)
PicoLisp
(de A
(27 . Jonah)
(18 . Alan)
(28 . Glory)
(18 . Popeye)
(28 . Alan) )
(de B
(Jonah . Whales)
(Jonah . Spiders)
(Alan . Ghosts)
(Alan . Zombies)
(Glory . Buffy) )
(for X B
(let K (cons (char (hash (car X))) (car X))
(if (idx 'M K T)
(push (caar @) (cdr X))
(set (car K) (list (cdr X))) ) ) )
(for X A
(let? Y (car (idx 'M (cons (char (hash (cdr X))) (cdr X))))
(for Z (caar Y)
(println (car X) (cdr X) (cdr Y) Z) ) ) )Output:
27 Jonah Jonah Spiders 27 Jonah Jonah Whales 18 Alan Alan Zombies 18 Alan Alan Ghosts 28 Glory Glory Buffy 28 Alan Alan Zombies 28 Alan Alan Ghosts
Plain TeX
Works with any TeX engine.
\newtoks\tabjoin
\def\quark{\quark}
\def\tabA{27:Jonah,18:Alan,28:Glory,18:Popeye,28:Alan}
\def\tabB{Jonah:Whales,Jonah:Spiders,Alan:Ghosts,Alan:Zombies,Glory:Buffy}
\def\mergejoin{\tabjoin{}\expandafter\mergejoini\tabA,\quark:\quark,}
\def\mergejoini#1:#2,{%
\ifx\quark#1\the\tabjoin
\else
\def\mergejoinii##1,#2:##2,{%
\ifx\quark##2\else
\tabjoin\expandafter{\the\tabjoin#1 : #2 : ##2\par}%
\expandafter\mergejoinii\expandafter,%
\fi
}%
\expandafter\mergejoinii\expandafter,\tabB,#2:\quark,%
\expandafter\mergejoini
\fi
}
\mergejoin
\bye
pdf or dvi output:
27 : Jonah : Whales 27 : Jonah : Spiders 18 : Alan : Ghosts 18 : Alan : Zombies 28 : Glory : Buffy 28 : Alan : Ghosts 28 : Alan : Zombies
Prolog
% Name/Age
person_age('Jonah', 27).
person_age('Alan', 18).
person_age('Glory', 28).
person_age('Popeye', 18).
person_age('Alan', 28).
% Character/Nemesis
character_nemisis('Jonah', 'Whales').
character_nemisis('Jonah', 'Spiders').
character_nemisis('Alan', 'Ghosts').
character_nemisis('Alan', 'Zombies').
character_nemisis('Glory', 'Buffy').
join_and_print :-
format('Age\tName\tCharacter\tNemisis\n\n'),
forall(
(person_age(Person, Age), character_nemisis(Person, Nemesis)),
format('~w\t~w\t~w\t\t~w\n', [Age, Person, Person, Nemesis])
).
- Output:
?- join_and_print. Age Name Character Nemisis 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 true.
PureBasic
Structure tabA
age.i
name.s
EndStructure
Structure tabB
char_name.s
nemesis.s
EndStructure
NewList listA.tabA()
NewList listB.tabB()
Macro SetListA(c_age, c_name)
AddElement(listA()) : listA()\age = c_age : listA()\name = c_name
EndMacro
Macro SetListB(c_char, c_nem)
AddElement(listB()) : listB()\char_name = c_char : listB()\nemesis = c_nem
EndMacro
SetListA(27, "Jonah") : SetListA(18, "Alan") : SetListA(28, "Glory")
SetListA(18, "Popeye") : SetListA(28, "Alan")
SetListB("Jonah", "Whales") : SetListB("Jonah", "Spiders")
SetListB("Alan", "Ghosts") : SetListB("Alan", "Zombies")
SetListB("Glory", "Buffy")
If OpenConsole("Hash_join")
ForEach listA()
PrintN("Input A = "+Str(listA()\age)+~"\t"+listA()\name)
Next
PrintN("")
ForEach listB()
PrintN("Input B = "+listB()\char_name+~"\t"+listB()\nemesis)
Next
PrintN(~"\nOutput\nA.Age\tA.Name\tB.Char.\tB.Nemesis")
ForEach listA()
ForEach listB()
If listA()\name = listB()\char_name
PrintN(Str(listA()\age)+~"\t"+listA()\name+~"\t"+
listB()\char_name+~"\t"+listB()\nemesis)
EndIf
Next
Next
Input()
EndIf
- Output:
Input A = 27 Jonah Input A = 18 Alan Input A = 28 Glory Input A = 18 Popeye Input A = 28 Alan Input B = Jonah Whales Input B = Jonah Spiders Input B = Alan Ghosts Input B = Alan Zombies Input B = Glory Buffy Output A.Age A.Name B.Char. 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
Python
from collections import defaultdict
def hashJoin(table1, index1, table2, index2):
h = defaultdict(list)
# hash phase
for s in table1:
h[s[index1]].append(s)
# join phase
return [(s, r) for r in table2 for s in h[r[index2]]]
table1 = [(27, "Jonah"),
(18, "Alan"),
(28, "Glory"),
(18, "Popeye"),
(28, "Alan")]
table2 = [("Jonah", "Whales"),
("Jonah", "Spiders"),
("Alan", "Ghosts"),
("Alan", "Zombies"),
("Glory", "Buffy")]
for row in hashJoin(table1, 1, table2, 0):
print(row)
- Output:
((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'))
Racket
#lang racket
(struct A (age name))
(struct B (name nemesis))
(struct AB (name age nemesis) #:transparent)
(define Ages-table
(list (A 27 "Jonah") (A 18 "Alan")
(A 28 "Glory") (A 18 "Popeye")
(A 28 "Alan")))
(define Nemeses-table
(list
(B "Jonah" "Whales") (B "Jonah" "Spiders")
(B "Alan" "Ghosts") (B "Alan" "Zombies")
(B "Glory" "Buffy")))
;; Hash phase
(define name->ages#
(for/fold ((rv (hash)))
((a (in-list Ages-table)))
(match-define (A age name) a)
(hash-update rv name (λ (ages) (append ages (list age))) null)))
;; Join phase
(for*/list
((b (in-list Nemeses-table))
(key (in-value (B-name b)))
(age (in-list (hash-ref name->ages# key))))
(AB key age (B-nemesis b)))
- Output:
(#(struct:AB "Jonah" 27 "Whales") #(struct:AB "Jonah" 27 "Spiders") #(struct:AB "Alan" 18 "Ghosts") #(struct:AB "Alan" 28 "Ghosts") #(struct:AB "Alan" 18 "Zombies") #(struct:AB "Alan" 28 "Zombies") #(struct:AB "Glory" 28 "Buffy"))
Raku
(formerly Perl 6)
The .classify method returns a multimap represented as a Hash whose values are Arrays.
sub hash-join(@a, &a, @b, &b) {
my %hash := @b.classify(&b);
@a.map: -> $a {
|(%hash{$a.&a} // next).map: -> $b { [$a, $b] }
}
}
my @A =
[27, "Jonah"],
[18, "Alan"],
[28, "Glory"],
[18, "Popeye"],
[28, "Alan"],
;
my @B =
["Jonah", "Whales"],
["Jonah", "Spiders"],
["Alan", "Ghosts"],
["Alan", "Zombies"],
["Glory", "Buffy"],
;
.say for hash-join @A, *[1], @B, *[0];
- Output:
[[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]]
REXX
/*REXX program demonstrates the classic hash join algorithm for two relations. */
S. = ; R. =
S.1 = 27 'Jonah' ; R.1 = "Jonah Whales"
S.2 = 18 'Alan' ; R.2 = "Jonah Spiders"
S.3 = 28 'Glory' ; R.3 = "Alan Ghosts"
S.4 = 18 'Popeye' ; R.4 = "Alan Zombies"
S.5 = 28 'Alan' ; R.5 = "Glory Buffy"
hash.= /*initialize the hash table (array). */
do #=1 while S.#\==''; parse var S.# age name /*extract information*/
hash.name=hash.name # /*build a hash table entry with its idx*/
end /*#*/ /* [↑] REXX does the heavy work here. */
#=#-1 /*adjust for the DO loop (#) overage.*/
do j=1 while R.j\=='' /*process a nemesis for a name element.*/
parse var R.j x nemesis /*extract the name and its nemesis. */
if hash.x=='' then do; #=# + 1 /*Not in hash? Then a new name; bump #*/
S.#=',' x /*add a new name to the S table. */
hash.x=# /* " " " " " " hash " */
end /* [↑] this DO isn't used today. */
do k=1 for words(hash.x); _=word(hash.x, k) /*obtain the pointer.*/
S._=S._ nemesis /*add the nemesis ──► applicable hash. */
end /*k*/
end /*j*/
_='─' /*the character used for the separator.*/
pad=left('', 4) /*spacing used in header and the output*/
say pad center('age', 3) pad center("name", 20 ) pad center('nemesis', 30 )
say pad center('───', 3) pad center("" , 20, _) pad center('' , 30, _)
do n=1 for #; parse var S.n age name nems /*obtain information.*/
if nems=='' then iterate /*No nemesis? Skip. */
say pad right(age,3) pad center(name,20) pad center(nems,30) /*display an "S". */
end /*n*/ /*stick a fork in it, we're all done. */
output when using the in-code relations (data):
age name nemesis
─── ──────────────────── ──────────────────────────────
27 Jonah Whales Spiders
18 Alan Ghosts Zombies
28 Glory Buffy
28 Alan Ghosts Zombies
Ring
Table1 = [[27, "Jonah"], [18, "Alan"], [28, "Glory"], [18, "Popeye"], [28, "Alan"]]
Table2 = [["Jonah", "Whales"], ["Jonah", "Spiders"], ["Alan", "Ghosts"], ["Alan", "Zombies"], ["Glory", "Buffy"]]
hTable = []
Qtable = []
for a in table1
h = hashing(a[2])
add(htable,[h , a])
next
for b in table2
h = hashing(b[1])
for sh in htable
if sh[1] = h
add(qtable, sh[2] + b[2])
ok
next
next
print(qtable)
#===============End of Execution=========
func print lst
see "---------------------------------------------------
Age | Name || Name | Nemesis
---------------------------------------------------
"
for l in lst
see string(l[1]) + char(9) + "| " + l[2] + copy(char(9),2) + "|| " + l[2] + " " + char(9) + "| " + l[3] + nl
next
func Hashing str
r = 0
if len(str) > 4
r = (ascii(str[1]) + ascii(str[len(str)]) + ascii(str[ceil(len(str) * 0.25)]) + ascii(str[ceil(len(str) * 0.75)]))
else
for s in str
r += ascii(s)
next
ok
return r- Output:
--------------------------------------------------- Age | Name || Name | Nemesis --------------------------------------------------- 27 | Jonah || Jonah | Whales 27 | Jonah || Jonah | Whales 18 | Alan || Alan | Ghosts 28 | Alan || Alan | Ghosts 18 | Alan || Alan | Ghosts 28 | Alan || Alan | Ghosts 28 | Glory || Glory | Buffy
Ruby
def hashJoin(table1, index1, table2, index2)
# hash phase
h = table1.group_by {|s| s[index1]}
h.default = []
# join phase
table2.collect {|r|
h[r[index2]].collect {|s| [s, r]}
}.flatten(1)
end
table1 = [[27, "Jonah"],
[18, "Alan"],
[28, "Glory"],
[18, "Popeye"],
[28, "Alan"]]
table2 = [["Jonah", "Whales"],
["Jonah", "Spiders"],
["Alan", "Ghosts"],
["Alan", "Zombies"],
["Glory", "Buffy"]]
hashJoin(table1, 1, table2, 0).each { |row| p row }
- Output:
[[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"]]
Run BASIC
sqliteconnect #mem, ":memory:"
#mem execute("CREATE TABLE t_age(age,name)")
#mem execute("CREATE TABLE t_name(name,nemesis)")
#mem execute("INSERT INTO t_age VALUES(27,'Jonah')")
#mem execute("INSERT INTO t_age VALUES(18,'Alan')")
#mem execute("INSERT INTO t_age VALUES(28,'Glory')")
#mem execute("INSERT INTO t_age VALUES(18,'Popeye')")
#mem execute("INSERT INTO t_age VALUES(28,'Alan')")
#mem execute("INSERT INTO t_name VALUES('Jonah','Whales')")
#mem execute("INSERT INTO t_name VALUES('Jonah','Spiders')")
#mem execute("INSERT INTO t_name VALUES('Alan','Ghosts')")
#mem execute("INSERT INTO t_name VALUES('Alan','Zombies')")
#mem execute("INSERT INTO t_name VALUES('Glory','Buffy')")
#mem execute("SELECT *,t_age.name FROM t_age LEFT JOIN t_name ON t_name.name = t_age.name")
WHILE #mem hasanswer()
#row = #mem #nextrow()
age = #row age()
name$ = #row name$()
nemesis$ = #row nemesis$()
print age;" ";name$;" ";nemesis$
WENDOutput:
27 Jonah Spiders 27 Jonah Whales 18 Alan Ghosts 18 Alan Zombies 28 Glory Buffy 18 Popeye 28 Alan Ghosts 28 Alan Zombies
Rust
use std::collections::HashMap;
use std::hash::Hash;
// If you know one of the tables is smaller, it is best to make it the second parameter.
fn hash_join<A, B, K>(first: &[(K, A)], second: &[(K, B)]) -> Vec<(A, K, B)>
where
K: Hash + Eq + Copy,
A: Copy,
B: Copy,
{
let mut hash_map = HashMap::new();
// hash phase
for &(key, val_a) in second {
// collect all values by their keys, appending new ones to each existing entry
hash_map.entry(key).or_insert_with(Vec::new).push(val_a);
}
let mut result = Vec::new();
// join phase
for &(key, val_b) in first {
if let Some(vals) = hash_map.get(&key) {
let tuples = vals.iter().map(|&val_a| (val_b, key, val_a));
result.extend(tuples);
}
}
result
}
fn main() {
let table1 = [("Jonah", 27), ("Alan", 18), ("Glory", 28), ("Popeye", 18), ("Alan", 28)];
let table2 = [
("Jonah", "Whales"), ("Jonah", "Spiders"), ("Alan", "Ghosts"),
("Alan", "Zombies"), ("Glory", "Buffy")
];
let result = hash_join(&table1, &table2);
println!("Age | Character Name | Nemesis");
println!("----|----------------|--------");
for (age, name, nemesis) in result {
println!("{:<3} | {:^14} | {}", age, name, nemesis);
}
}
- Output:
Age | Character Name | Nemesis ----|----------------|-------- 27 | Jonah | Whales 27 | Jonah | Spiders 18 | Alan | Ghosts 18 | Alan | Zombies 28 | Glory | Buffy 28 | Alan | Ghosts 28 | Alan | Zombies
Scala
def join[Type](left: Seq[Seq[Type]], right: Seq[Seq[Type]]) = {
val hash = right.groupBy(_.head) withDefaultValue Seq()
left.flatMap(cols => hash(cols.last).map(cols ++ _.tail))
}
// Example:
val table1 = List(List("27", "Jonah"),
List("18", "Alan"),
List("28", "Glory"),
List("18", "Popeye"),
List("28", "Alan"))
val table2 = List(List("Jonah", "Whales"),
List("Jonah", "Spiders"),
List("Alan", "Ghosts"),
List("Alan", "Zombies"),
List("Glory", "Buffy"))
println(join(table1, table2) mkString "\n")
- Output:
List(27, Jonah, Whales) List(27, Jonah, Spiders) List(18, Alan, Ghosts) List(18, Alan, Zombies) List(28, Glory, Buffy) List(28, Alan, Ghosts) List(28, Alan, Zombies)
Scheme
(use srfi-42)
(define ages '((27 Jonah) (18 Alan) (28 Glory) (18 Popeye) (28 Alan)))
(define nemeses '((Jonah Whales) (Jonah Spiders) (Alan Ghosts)
(Alan Zombies) (Glory Buffy)
(unknown nothing)))
(define hash (make-hash-table 'equal?))
(dolist (item ages)
(hash-table-push! hash (last item) (car item)))
(do-ec
(: person nemeses)
(:let name (car person))
(if (hash-table-exists? hash name))
(: age (~ hash name))
(print (list (list age name)
person)))
- Output:
((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))
Sidef
func hashJoin(table1, index1, table2, index2) {
var a = []
var h = Hash()
# hash phase
table1.each { |s|
h{s[index1]} := [] << s
}
# join phase
table2.each { |r|
a += h{r[index2]}.map{[_,r]}
}
return a
}
var t1 = [[27, "Jonah"],
[18, "Alan"],
[28, "Glory"],
[18, "Popeye"],
[28, "Alan"]]
var t2 = [["Jonah", "Whales"],
["Jonah", "Spiders"],
["Alan", "Ghosts"],
["Alan", "Zombies"],
["Glory", "Buffy"]]
hashJoin(t1, 1, t2, 0).each { .say }
- Output:
[[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']]
SQL
-- setting up the test data
create table people (age number(3), name varchar2(30));
insert into people (age, name)
select 27, 'Jonah' from dual union all
select 18, 'Alan' from dual union all
select 28, 'Glory' from dual union all
select 18, 'Popeye' from dual union all
select 28, 'Alan' from dual
;
create table nemesises (name varchar2(30), nemesis varchar2(30));
insert into nemesises (name, nemesis)
select 'Jonah', 'Whales' from dual union all
select 'Jonah', 'Spiders' from dual union all
select 'Alan' , 'Ghosts' from dual union all
select 'Alan' , 'Zombies' from dual union all
select 'Glory', 'Buffy' from dual
;
Doing the join is trivial. Normally we would let the optimizer select the join method. However, to force a hash join, we can use an optimizer hint, USE_HASH.
select /*+ use_hash */ * from people join nemesises using(name);
- Output:
AGE NAME NEMESIS ---- ---------------- ---------------- 27 Jonah Whales 27 Jonah Spiders 28 Alan Ghosts 18 Alan Ghosts 28 Alan Zombies 18 Alan Zombies 28 Glory Buffy
Swift
func hashJoin<A, B, K: Hashable>(_ first: [(K, A)], _ second: [(K, B)]) -> [(A, K, B)] {
var map = [K: [B]]()
for (key, val) in second {
map[key, default: []].append(val)
}
var res = [(A, K, B)]()
for (key, val) in first {
guard let vals = map[key] else {
continue
}
res += vals.map({ (val, key, $0) })
}
return res
}
let t1 = [
("Jonah", 27),
("Alan", 18),
("Glory", 28),
("Popeye", 18),
("Alan", 28)
]
let t2 = [
("Jonah", "Whales"),
("Jonah", "Spiders"),
("Alan", "Ghosts"),
("Alan", "Zombies"),
("Glory", "Buffy")
]
print("Age | Character Name | Nemesis")
print("----|----------------|--------")
for (age, name, nemesis) in hashJoin(t1, t2) {
print("\(age) | \(name) | \(nemesis)")
}
- Output:
Age | Character Name | Nemesis ----|----------------|-------- 27 | Jonah | Whales 27 | Jonah | Spiders 18 | Alan | Ghosts 18 | Alan | Zombies 28 | Glory | Buffy 28 | Alan | Ghosts 28 | Alan | Zombies
Tcl
Tcl uses hash tables to implement both its associative arrays and its dictionaries.
package require Tcl 8.6
# Only for lmap, which can be replaced with foreach
proc joinTables {tableA a tableB b} {
# Optimisation: if the first table is longer, do in reverse order
if {[llength $tableB] < [llength $tableA]} {
return [lmap pair [joinTables $tableB $b $tableA $a] {
lreverse $pair
}]
}
foreach value $tableA {
lappend hashmap([lindex $value $a]) [lreplace $value $a $a]
#dict version# dict lappend hashmap [lindex $value $a] [lreplace $value $a $a]
}
set result {}
foreach value $tableB {
set key [lindex $value $b]
if {![info exists hashmap($key)]} continue
#dict version# if {![dict exists $hashmap $key]} continue
foreach first $hashmap($key) {
#dict version# foreach first [dict get $hashmap $key]
lappend result [list {*}$first $key {*}[lreplace $value $b $b]]
}
}
return $result
}
set tableA {
{27 "Jonah"} {18 "Alan"} {28 "Glory"} {18 "Popeye"} {28 "Alan"}
}
set tableB {
{"Jonah" "Whales"} {"Jonah" "Spiders"} {"Alan" "Ghosts"} {"Alan" "Zombies"}
{"Glory" "Buffy"}
}
set joined [joinTables $tableA 1 $tableB 0]
foreach row $joined {
puts $row
}
- Output:
27 Jonah Whales 27 Jonah Spiders 18 Alan Ghosts 28 Alan Ghosts 18 Alan Zombies 28 Alan Zombies 28 Glory Buffy
TXR
Generic hash join. Arguments left-key and right-key are functions applied to the elements of the left and right sequences to retrieve the join key.
(defvar age-name '((27 Jonah)
(18 Alan)
(28 Glory)
(18 Popeye)
(28 Alan)))
(defvar nemesis-name '((Jonah Whales)
(Jonah Spiders)
(Alan Ghosts)
(Alan Zombies)
(Glory Buffy)))
(defun hash-join (left left-key right right-key)
(let ((join-hash [group-by left-key left])) ;; hash phase
(append-each ((r-entry right)) ;; join phase
(collect-each ((l-entry [join-hash [right-key r-entry]]))
^(,l-entry ,r-entry)))))
(format t "~s\n" [hash-join age-name second nemesis-name first])- Output:
$ txr hash-join.tl (((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)))
VBScript
Dim t_age(4,1)
t_age(0,0) = 27 : t_age(0,1) = "Jonah"
t_age(1,0) = 18 : t_age(1,1) = "Alan"
t_age(2,0) = 28 : t_age(2,1) = "Glory"
t_age(3,0) = 18 : t_age(3,1) = "Popeye"
t_age(4,0) = 28 : t_age(4,1) = "Alan"
Dim t_nemesis(4,1)
t_nemesis(0,0) = "Jonah" : t_nemesis(0,1) = "Whales"
t_nemesis(1,0) = "Jonah" : t_nemesis(1,1) = "Spiders"
t_nemesis(2,0) = "Alan" : t_nemesis(2,1) = "Ghosts"
t_nemesis(3,0) = "Alan" : t_nemesis(3,1) = "Zombies"
t_nemesis(4,0) = "Glory" : t_nemesis(4,1) = "Buffy"
Call hash_join(t_age,1,t_nemesis,0)
Sub hash_join(table_1,index_1,table_2,index_2)
Set hash = CreateObject("Scripting.Dictionary")
For i = 0 To UBound(table_1)
hash.Add i,Array(table_1(i,0),table_1(i,1))
Next
For j = 0 To UBound(table_2)
For Each key In hash.Keys
If hash(key)(index_1) = table_2(j,index_2) Then
WScript.StdOut.WriteLine hash(key)(0) & "," & hash(key)(1) &_
" = " & table_2(j,0) & "," & table_2(j,1)
End If
Next
Next
End Sub
- Output:
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
Visual FoxPro
Hashing using the common key (name) gives ambiguous results as the name column is not unique in either table (a unique key could be formed by using the age and name columns) . This implementation forces a unique key on the people table.
LOCAL i As Integer, n As Integer
CLOSE DATABASES ALL
*!* Create and populate the hash tables
CREATE CURSOR people_ids(id I, used L DEFAULT .F.)
INDEX ON id TAG id COLLATE "Machine"
INDEX ON used TAG used BINARY COLLATE "Machine"
SET ORDER TO 0
CREATE CURSOR nem_ids(id I, used L DEFAULT .F.)
INDEX ON id TAG id COLLATE "Machine"
INDEX ON used TAG used BINARY COLLATE "Machine"
SET ORDER TO 0
n = 100
FOR i = 1 TO n
INSERT INTO people_ids (id) VALUES (i)
INSERT INTO nem_ids (id) VALUES (i)
ENDFOR
CREATE CURSOR people (age I, name V(16), id I)
INDEX ON id TAG id COLLATE "Machine"
INDEX ON name TAG name COLLATE "Machine"
SET ORDER TO 0
INSERT INTO people (age, name) VALUES (27, "Jonah")
INSERT INTO people (age, name) VALUES (18, "Alan")
INSERT INTO people (age, name) VALUES (28, "Glory")
INSERT INTO people (age, name) VALUES (18, "Popeye")
INSERT INTO people (age, name) VALUES (28, "Alan")
REPLACE id WITH HashMe("people_ids") ALL
*!* The plural of nemesis is nemeses
CREATE CURSOR nemeses (name V(16), nemesis V(16), p_id I, id I)
INDEX ON id TAG id COLLATE "Machine"
INDEX ON p_id TAG p_id COLLATE "Machine"
INDEX ON name TAG name COLLATE "Machine"
SET ORDER TO 0
INSERT INTO nemeses (name, nemesis) VALUES ("Jonah", "Whales")
INSERT INTO nemeses (name, nemesis) VALUES ("Jonah", "Spiders")
INSERT INTO nemeses (name, nemesis) VALUES ("Alan", "Ghosts")
INSERT INTO nemeses (name, nemesis) VALUES ("Alan", "Zombies")
INSERT INTO nemeses (name, nemesis) VALUES ("Glory", "Buffy")
REPLACE id WITH HashMe("nem_ids") ALL
UPDATE nemeses SET p_id = people.id FROM people ;
WHERE nemeses.name = people.name
*!* Show the join
SELECT pe.age, pe.name, ne.nemesis FROM people pe ;
JOIN nemeses ne ON pe.id = ne.p_id TO FILE "hashjoin.txt"
FUNCTION HashMe(cTable As String) As Integer
LOCAL ARRAY a[1]
SELECT MIN(id) FROM (cTable) WHERE NOT used INTO ARRAY a
UPDATE (cTable) SET used = .T. WHERE id = a[1]
RETURN a[1]
ENDFUNC
- Output:
AGE NAME NEMESIS 27 Jonah Whales 27 Jonah Spiders 18 Alan Ghosts 18 Alan Zombies 28 Glory Buffy
Wren
import "./fmt" for Fmt
class A {
construct new(age, name) {
_age = age
_name = name
}
age { _age }
name { _name }
}
class B {
construct new(character, nemesis) {
_character = character
_nemesis = nemesis
}
character { _character }
nemesis { _nemesis }
}
var tableA = [
A.new(27, "Jonah"), A.new(18, "Alan"), A.new(28, "Glory"),
A.new(18, "Popeye"), A.new(28, "Alan")
]
var tableB = [
B.new("Jonah", "Whales"), B.new("Jonah", "Spiders"), B.new("Alan", "Ghosts"),
B.new("Alan", "Zombies"), B.new("Glory", "Buffy")
]
var h = {}
var i = 0
for (a in tableA) {
var n = h[a.name]
if (n) {
n.add(i)
} else {
h[a.name] = [i]
}
i = i + 1
}
System.print("Age Name Character Nemesis")
System.print("--- ----- --------- -------")
for (b in tableB) {
var c = h[b.character]
if (c) {
for (i in c) {
var t = tableA[i]
Fmt.print("$3d $-5s $-9s $s", t.age, t.name, b.character, b.nemesis)
}
}
}
- Output:
Age Name Character Nemesis --- ----- --------- ------- 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
zkl
Join two tables by hashing on the common key (name). The resulting join is the intersection of the two tables.
ageName:=T(27,"Jonah", 18,"Alan", 28,"Glory", 18,"Popeye", 28,"Alan");
nameNemesis:=T("Jonah","Whales", "Jonah","Spiders", "Alan","Ghosts",
"Alan","Zombies", "Glory","Buffy");
fcn addAN(age,name,d){ // keys are names, values are ( (age,...),() )
if (r:=d.find(name)) d[name] = T(r[0].append(age),r[1]);
else d.add(name,T(T(age),T));
d // return d so pump will use that as result for assignment
}
fcn addNN(name,nemesis,d){ // values-->( (age,age...), (nemesis,...) )
if (r:=d.find(name)){
ages,nemesises := r;
d[name] = T(ages,nemesises.append(nemesis));
}
}
// Void.Read --> take existing i, read next one, pass both to next function
var d=ageName.pump(Void,Void.Read,T(addAN,Dictionary()));
nameNemesis.pump(Void,Void.Read,T(addNN,d));
d.println(); // the union of the two tables
d.keys.sort().pump(Console.println,'wrap(name){ //pretty print the join
val:=d[name]; if (not val[1])return(Void.Skip);
String(name,":",d[name][1].concat(","));
})zkl Dictionaries only have one key
D(Popeye:L(L(18),L()),Glory:L(L(28),L("Buffy")),
Jonah:L(L(27),L("Whales","Spiders")),Alan:L(L(18,28),L("Ghosts","Zombies")))
Alan:Ghosts,Zombies
Glory:Buffy
Jonah:Whales,Spiders
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