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.
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 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 do
place b in multimap MB under key b(jB)
for each row a in table A do
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
| 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"]].
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.
<lang bracmat>( (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)
)
)
)
& );</lang> 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
<lang csharp>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;
}
}
}</lang>
- 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
Clojure
<lang 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))) </lang>
- 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
<lang 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))))</lang>
- 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
<lang 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][]);
}</lang>
- 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
<lang dejavu>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</lang>
- 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" ] ]
EchoLisp
Since this is a real, professional application, we build the hash tables in permanent (local) storage. <lang lisp> (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)) </lang>
- Output:
<lang lisp> (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") </lang>
ECL
<lang 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
- /
</lang>
Elixir
<lang 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)</lang>
- 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
<lang 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]. </lang>
- 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"}}]
Forth
Works with any ANS Forth
Needs the FMS-SI (single inheritance) library code located here: http://soton.mpeforth.com/flag/fms/index.html <lang forth> 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:
</lang>
- Output:
o{
o{ 27 'Jonah' Whales Spiders Vampires }
o{ 18 'Alan' Ghosts Zombies }
o{ 28 'Glory' Buffy }
o{ 28 'Alan' Ghosts Zombies } }
Go
<lang 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)
}
}
}</lang>
- 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: <lang Groovy> 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
} </lang>
More functional style: <lang Groovy> 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()
} </lang>
Sample run (either version as the result is the same): <lang Groovy> 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 } </lang>
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. <lang Haskell>{-# 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
</lang>
((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): <lang Haskell>{-# 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
</lang>
((1,"Jonah"),("Jonah","Spiders"))
((1,"Jonah"),("Jonah","Whales"))
((2,"Alan"),("Alan","Zombies"))
((2,"Alan"),("Alan","Ghosts"))
((3,"Glory"),("Glory","Buffy"))
J
Data:
<lang J>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
)</lang>
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:
<lang J>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</lang>
Result:
<lang J> JOIN ┌─────┬──┬───────┐ │Jonah│27│Whales │ ├─────┼──┼───────┤ │Jonah│27│Spiders│ ├─────┼──┼───────┤ │Alan │18│Ghosts │ ├─────┼──┼───────┤ │Alan │18│Zombies│ ├─────┼──┼───────┤ │Alan │28│Ghosts │ ├─────┼──┼───────┤ │Alan │28│Zombies│ ├─────┼──┼───────┤ │Glory│28│Buffy │ └─────┴──┴───────┘</lang>
Java
<lang 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; }
}</lang>
[[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]]
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
<lang jq># 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)
- </lang>
Example <lang jq>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</lang>
- Output:
<lang sh>$ 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"]</lang>
hashJoinArrays
<lang jq># 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] + $row[index2+1:] ] )
else . end)
- </lang>
Example
In the following example, the previously defined pretty-print function (pp) and tables (table1 and table2) are used, so their definitions are not repeated here. <lang jq>hashJoinArrays(table1; 1; table2; 0) | pp</lang>
- Output:
<lang sh>$ jq -c -r -n -f HashJoinArrays.jq
[27,"Jonah","Whales"] [27,"Jonah","Spiders"] [28,"Alan","Ghosts"] [28,"Alan","Zombies"] [28,"Glory","Buffy"]</lang>
LFE
<lang lisp> (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)))))
</lang>
Table definitions in the LFE REPL: <lang lisp> > (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"))))
</lang>
Output in LFE REPL: <lang lisp> > (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"))))
</lang>
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 <lang mathematica>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@table11,table1colindex],table1colindex]]],table1]; t2=If[table2colindex != 1, table2[[All,Prepend[Delete[Range@Length@table21,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[t11]+Length[t21]-1] ];</lang> 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
Oberon-2
Works with oo2c version 2 <lang oberon2> 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. </lang> 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: <lang ocaml>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)</lang>
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
<lang 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";
}</lang>
- 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']];
Perl 6
The .classify method returns a multimap represented as a Hash whose values are Arrays.
<lang perl6>sub hash-join(@a, &a, @b, &b) {
my %hash := @b.classify(&b);
@a.map: -> $a {
|(%hash{a $a} // next).map: -> $b { [$a, $b] }
}
}</lang>
Testing:
<lang perl6>my @A =
[27, "Jonah"], [18, "Alan"], [28, "Glory"], [18, "Popeye"], [28, "Alan"],
my @B =
["Jonah", "Whales"], ["Jonah", "Spiders"], ["Alan", "Ghosts"], ["Alan", "Zombies"], ["Glory", "Buffy"],
.say for hash-join @A, *[1], @B, *[0];</lang>
- Output:
[[27 Jonah] [Jonah Whales]] [[27 Jonah] [Jonah Spiders]] [[18 Alan] [Alan Ghosts]] [[18 Alan] [Alan Zombies]] [[28 Glory] [Glory Buffy]] [[28 Alan] [Alan Ghosts]] [[28 Alan] [Alan Zombies]]
PHP
<lang php><?php function hashJoin($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);
?></lang>
- 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
)
)
Python
<lang 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)</lang>
- 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>#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)))</lang>
- 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"))
REXX
<lang 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. */</lang>
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
<lang 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</lang>
- 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
<lang 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 }</lang>
- 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
<lang Runbasic>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$ WEND</lang>Output:
27 Jonah Spiders 27 Jonah Whales 18 Alan Ghosts 18 Alan Zombies 28 Glory Buffy 18 Popeye 28 Alan Ghosts 28 Alan Zombies
Rust
<lang rust> use std::collections::HashMap;
fn main() {
let table_a = vec![
(27, "Jonah"), (18, "Alan"), (28, "Glory"),
(18, "Popeye"), (28, "Alan")
];
let table_b = vec![
("Jonah", "Whales"), ("Jonah", "Spiders"), ("Alan", "Ghosts"),
("Alan", "Zombies"), ("Glory", "Buffy")
];
// hash phase
let mut h = HashMap::new();
for (i, a) in table_a.iter().enumerate() {
h.entry(a.1).or_insert(vec![]).push(i);
}
// join phase
for b in table_b {
for i in h.get(b.0).unwrap_or(&vec![]) {
let a = table_a.get(*i).unwrap();
println!("{:?} {:?}", a, b);
}
}
} </lang>
- 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")
Scala
<lang 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")</lang>
- 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
<lang 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)))
</lang>
- 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
<lang ruby>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 }</lang>
- 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 data is a bit verbose: <lang sql>create table people (age decimal(3), name varchar(16)); 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');
create table nemesises (name varchar(16), nemesis varchar(16)); insert into nemesises (name, nemesis) values ('Jonah', 'Whales'); insert into nemesises (name, nemesis) values ('Jonah', 'Spiders'); insert into nemesises (name, nemesis) values ('Alan', 'Ghosts'); insert into nemesises (name, nemesis) values ('Alan', 'Zombies'); insert into nemesises (name, nemesis) values ('Glory', 'Buffy');</lang>
Doing the join is concise. But we don't actually have control over how the join is implemented, so this might not actually be a hash join... <lang sql>select * from people p join nemesises n on p.name = n.name</lang>
- Output:
AGE NAME NAME NEMESIS
---------- ---------------- ---------------- ----------------
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
Tcl
Tcl uses hash tables to implement both its associative arrays and its dictionaries. <lang tcl>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
}</lang>
- 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.
<lang txrlisp>(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])</lang>
- 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
<lang vb> 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 </lang>
- 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. <lang vfp> 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 </lang>
- Output:
AGE NAME NEMESIS 27 Jonah Whales 27 Jonah Spiders 18 Alan Ghosts 18 Alan Zombies 28 Glory Buffy
zkl
Join two tables by hashing on the common key (name). The resulting join is the intersection of the two tables. <lang zkl>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(","));
})</lang> 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