Sorting¶
Miller gives you three ways to sort your data:
- The
sort
verb lets you sort records (rows) by various fields (columns). - The
sort-within-records
verb lets you sort fields within records. - The
sort
DSL function gives you more customizable options for sorting data either within fields or across records. (See also the higher-order-functions page for related information.)
Sorting records: the sort verb¶
The sort
verb (see its documentation for more information) reorders
entire records within the data stream. You can sort lexically (with or without case-folding),
numerically, or naturally (see
https://en.wikipedia.org/wiki/Natural_sort_order
or https://github.com/facette/natsort for more about natural
sorting); ascending or descending; and you can sort primarily by one column, then secondarily by
another, etc.
Input data:
mlr --c2p cat example.csv
color shape flag k index quantity rate yellow triangle true 1 11 43.6498 9.8870 red square true 2 15 79.2778 0.0130 red circle true 3 16 13.8103 2.9010 red square false 4 48 77.5542 7.4670 purple triangle false 5 51 81.2290 8.5910 red square false 6 64 77.1991 9.5310 purple triangle false 7 65 80.1405 5.8240 yellow circle true 8 73 63.9785 4.2370 yellow circle true 9 87 63.5058 8.3350 purple square false 10 91 72.3735 8.2430
Sorted numerically ascending by rate:
mlr --c2p sort -n rate example.csv
color shape flag k index quantity rate red square true 2 15 79.2778 0.0130 red circle true 3 16 13.8103 2.9010 yellow circle true 8 73 63.9785 4.2370 purple triangle false 7 65 80.1405 5.8240 red square false 4 48 77.5542 7.4670 purple square false 10 91 72.3735 8.2430 yellow circle true 9 87 63.5058 8.3350 purple triangle false 5 51 81.2290 8.5910 red square false 6 64 77.1991 9.5310 yellow triangle true 1 11 43.6498 9.8870
Sorted lexically ascending by color; then, within each color, numerically descending by quantity:
mlr --c2p sort -f color -nr quantity example.csv
color shape flag k index quantity rate purple triangle false 5 51 81.2290 8.5910 purple triangle false 7 65 80.1405 5.8240 purple square false 10 91 72.3735 8.2430 red square true 2 15 79.2778 0.0130 red square false 4 48 77.5542 7.4670 red square false 6 64 77.1991 9.5310 red circle true 3 16 13.8103 2.9010 yellow circle true 8 73 63.9785 4.2370 yellow circle true 9 87 63.5058 8.3350 yellow triangle true 1 11 43.6498 9.8870
Example of natural sort, adapted from https://github.com/facette/natsort:
mlr --c2p cat data/natsort.csv
n name 1 Allegia 51 Clasteron 2 Callisto Morphamax 6000 SE 3 Xiph Xlater 58 4 1000X Radonius Maximus 5 20X Radonius Prime 6 30X Radonius 7 Alpha 2 8 Allegia 50 Clasteron 9 Alpha 2A-8000 10 200X Radonius 11 Allegia 50B Clasteron 12 Xiph Xlater 5 13 Callisto Morphamax 700 14 Xiph Xlater 500 15 Alpha 2A-900 16 20X Radonius 17 Callisto Morphamax 6000 SE2 18 Allegia 500 Clasteron 19 Alpha 100 20 Alpha 2A 21 Xiph Xlater 300 22 Callisto Morphamax 23 Callisto Morphamax 7000 24 10X Radonius 25 Xiph Xlater 40 26 Allegia 6R Clasteron 27 Callisto Morphamax 5000
mlr --c2p sort -t name data/natsort.csv
n name 24 10X Radonius 16 20X Radonius 5 20X Radonius Prime 6 30X Radonius 10 200X Radonius 4 1000X Radonius Maximus 26 Allegia 6R Clasteron 8 Allegia 50 Clasteron 11 Allegia 50B Clasteron 1 Allegia 51 Clasteron 18 Allegia 500 Clasteron 7 Alpha 2 20 Alpha 2A 15 Alpha 2A-900 9 Alpha 2A-8000 19 Alpha 100 22 Callisto Morphamax 13 Callisto Morphamax 700 27 Callisto Morphamax 5000 2 Callisto Morphamax 6000 SE 17 Callisto Morphamax 6000 SE2 23 Callisto Morphamax 7000 12 Xiph Xlater 5 25 Xiph Xlater 40 3 Xiph Xlater 58 21 Xiph Xlater 300 14 Xiph Xlater 500
Sorting fields within records: the sort-within-records verb¶
The sort-within-records
verb (see its
documentation for more information)
leaves records in their original order in the data stream, but reorders fields
within each record. A typical use-case is for given all records the same column-ordering,
in particular for converting JSON to CSV (or other tabular formats):
cat data/sort-within-records.json
{ "a": 1, "b": 2, "c": 3 } { "b": 4, "a": 5, "c": 6 } { "c": 7, "b": 8, "a": 9 }
mlr --ijson --opprint cat data/sort-within-records.json
a b c 1 2 3 b a c 4 5 6 c b a 7 8 9
mlr --ijson --opprint sort-within-records data/sort-within-records.json
a b c 1 2 3 5 4 6 9 8 7
The sort function by example¶
The Miller DSL has a sort
function:
- It returns a sorted copy of an input array or map.
- Without second argument, uses Miller's default ordering which is numbers numerically, then strings lexically.
- With second which is string, takes sorting flags from it:
"f"
for lexical or"c"
for case-folded lexical, or"t"
for natural sort order. An additional"r"
in this string is for reverse/descending.
mlr -n put ' end { # Sort array with default ordering print sort([5,2,3,1,4]); } '
[1, 2, 3, 4, 5]
mlr -n put ' end { # Sort array with reverse-default ordering print sort([5,2,3,1,4], "r"); } '
[5, 4, 3, 2, 1]
mlr -n put ' end { # Sort array with custom function: another way to get default ordering print sort([5,2,3,1,4], func(a,b) { return a <=> b}); } '
[1, 2, 3, 4, 5]
mlr -n put ' end { # Sort array with custom function: another way to get reverse-default ordering print sort([5,2,3,1,4], func(a,b) { return b <=> a}); } '
[5, 4, 3, 2, 1]
mlr -n put ' end { # Sort map with default ordering on keys print sort({"c":2, "a": 3, "b": 1}); } '
{ "a": 3, "b": 1, "c": 2 }
mlr -n put ' end { # Sort map with reverse-default ordering on keys print sort({"c":2, "a": 3, "b": 1}, "r"); } '
{ "c": 2, "b": 1, "a": 3 }
mlr -n put ' end { # Sort map with custom function: default ordering on values print sort({"c":2, "a": 3, "b": 1}, "v"); # Same: print sort({"c":2, "a": 3, "b": 1}, func(ak,av,bk,bv) {return av <=> bv}); } '
{ "b": 1, "c": 2, "a": 3 } { "b": 1, "c": 2, "a": 3 }
mlr -n put ' end { # Sort map with custom function: reverse-default ordering on values print sort({"c":2, "a": 3, "b": 1}, "vr"); # Same: print sort({"c":2, "a": 3, "b": 1}, func(ak,av,bk,bv){return bv <=> av}); } '
{ "a": 3, "c": 2, "b": 1 } { "a": 3, "c": 2, "b": 1 }
mlr -n put ' end { # Natural sort print sort(["a1","a10","a100","a2","a20","a200"], "t"); } '
["a1", "a2", "a10", "a20", "a100", "a200"]
In the rest of this page we'll look more closely at these variants.
Simple sorting of arrays¶
Using the sort
function, you can
get a copy of an array, sorted by its values -- optionally, with reversed
order, and/or lexical/case-folded sorting. The first argument is an array to be
sorted. The optional second argument is a string containing any of the
characters n
for numeric (the default anyway), f
for lexical, or c
for
case-folded lexical, and r
for reverse. Note that sort
does not modify
its argument; it returns a sorted copy.
Also note that all the flags to sort
allow you to operate on arrays which
contain strings, floats, and booleans; if you need to sort an array whose
values are themselves maps or arrays, you'll need sort
with function argument
as described further down in this page.
cat data/sorta-example.csv
key,values alpha,4;6;1;5 beta,7;9;9;8 gamma,11;2;1;12
Default sort is numerical ascending:
mlr --c2p --from data/sorta-example.csv put ' $values = splita($values, ";"); $values = sort($values); # default flags $values = joinv($values, ";"); '
key values alpha 1;4;5;6 beta 7;8;9;9 gamma 1;2;11;12
Use the "r"
flag for reverse, which is numerical descending:
mlr --c2p --from data/sorta-example.csv put ' $values = splita($values, ";"); $values = sort($values, "r"); # 'r' flag for reverse sort $values = joinv($values, ";"); '
key values alpha 6;5;4;1 beta 9;9;8;7 gamma 12;11;2;1
Use the "f"
flag for lexical ascending sort (and "fr"
would lexical descending):
mlr --c2p --from data/sorta-example.csv put ' $values = splita($values, ";"); $values = sort($values, "f"); # 'f' flag for lexical sort $values = joinv($values, ";"); '
key values alpha 1;4;5;6 beta 7;8;9;9 gamma 1;11;12;2
Without and with case-folding:
cat data/sorta-example-text.csv
key,values alpha,cat;bat;Australia;Bavaria;apple;Colombia alpha,cat;bat;Australia;Bavaria;apple;Colombia
mlr --c2p --from data/sorta-example-text.csv put ' $values = splita($values, ";"); if (NR == 1) { $values = sort($values, "f"); # 'f' flag for (non-folded) lexical sort } else { $values = sort($values, "c"); # 'c' flag for case-folded lexical sort } $values = joinv($values, ";"); '
key values alpha Australia;Bavaria;Colombia;apple;bat;cat alpha apple;Australia;bat;Bavaria;cat;Colombia
Simple sorting of maps within records¶
Using the sort
function, you
can sort a map by its keys.
Since sort
only gives you options for sorting a map by its keys, if you want
to sort a map by its values you'll need sort
with function argument as
described further down in this page.
Also note that, unlike the sort-within-record
verb with its -r
flag,
sort
doesn't recurse into submaps and sort those.
cat data/server-log.json
{ "hostname": "localhost", "pid": 12345, "req": { "id": 6789, "method": "GET", "path": "api/check", "host": "foo.bar", "headers": { "host": "bar.baz", "user-agent": "browser" } }, "res": { "status_code": 200, "header": { "content-type": "text", "content-encoding": "plain" } } }
mlr --json --from data/server-log.json put ' $req = sort($req); # Ascending here $res = sort($res, "r"); # Descending here '
[ { "hostname": "localhost", "pid": 12345, "req": { "headers": { "host": "bar.baz", "user-agent": "browser" }, "host": "foo.bar", "id": 6789, "method": "GET", "path": "api/check" }, "res": { "status_code": 200, "header": { "content-type": "text", "content-encoding": "plain" } } } ]
Simple sorting of maps across records¶
As discussed in the page on
operating on all records, while Miller is normally
streaming (we operate on one record at a time), we
can accumulate records in an array-valued or map-valued
out-of-stream variable,
then operate on that record-list in an end
block. This includes the possibility
of accumulating records in a map, then sorting the map.
Using the f
flag we're sorting the map keys (1-up NR) lexically, so we
have 1, then 10, then 2:
mlr --icsv --opprint --from example.csv put -q ' begin { @records = {}; # Define as a map } $nr = NR; @records[NR] = $*; # Accumulate end { @records = sort(@records, "f"); for (_, record in @records) { emit1 record; } } '
color shape flag k index quantity rate nr yellow triangle true 1 11 43.6498 9.8870 1 purple square false 10 91 72.3735 8.2430 10 red square true 2 15 79.2778 0.0130 2 red circle true 3 16 13.8103 2.9010 3 red square false 4 48 77.5542 7.4670 4 purple triangle false 5 51 81.2290 8.5910 5 red square false 6 64 77.1991 9.5310 6 purple triangle false 7 65 80.1405 5.8240 7 yellow circle true 8 73 63.9785 4.2370 8 yellow circle true 9 87 63.5058 8.3350 9
Custom sorting of arrays within records¶
Using the sort
function, you
can sort an array by its values, using another function (which you specify --
see the page on user-defined functions)
for comparing elements.
- Your function must take two arguments, which will range over various pairs of values in your array;
- It must return a number which is negative, zero, or positive depending on whether you want the first argument to sort less than, equal to, or greater than the second, respectively.
For example, let's use the following input data. Instead of having an array, it has some semicolon-delimited data in a field which we can split and sort:
cat data/sortaf-example.csv
key,values alpha,5;2;8;6;1;4;9;10;3;7
In the following example we sort data in several ways -- the first two just
recapitulate (for reference) what sort
with default flags already does; the third is novel:
mlr --icsv --ojson --from data/sortaf-example.csv put ' # Same as sort($values) func forward(a,b) { return a <=> b } # Same as sort($values, "r") func reverse(a,b) { return b <=> a } # Custom sort func even_then_odd(a,b) { ax = a % 2; bx = b % 2; if (ax == bx) { return a <=> b } elif (bx == 1) { return -1 } else { return 1 } } split_values = splita($values, ";"); $forward = sort(split_values, forward); $reverse = sort(split_values, reverse); $even_then_odd = sort(split_values, even_then_odd); '
[ { "key": "alpha", "values": "5;2;8;6;1;4;9;10;3;7", "forward": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "reverse": [10, 9, 8, 7, 6, 5, 4, 3, 2, 1], "even_then_odd": [2, 4, 6, 8, 10, 1, 3, 5, 7, 9] } ]
Custom sorting of arrays across records¶
As noted above, we can use the
operating-on-all-records paradigm
to accumulate records in an array-valued or map-valued
out-of-stream variable,
then operate on that record-list in an end
block. This includes the possibility
of accumulating records in an array, then sorting the array.
Note that here the array elements are maps, so the a
and b
arguments to our
functions are maps -- and we have to access the index
field using either
a["index"]
and b["index"]
, or (using the dot operator for
indexing)
a.index
and b.index
.
mlr --icsv --opprint --from example.csv put -q ' # Sort primarily ascending on the shape field, then secondarily # descending numeric on the index field. func cmp(a, b) { cmp1 = a.shape <=> b.shape; if (cmp1 != 0) { return cmp1 } else { return b.index <=> a.index; } } begin { @records = []; # Define as an array, else auto-create will make a map } @records[NR] = $*; # Accumulate end { @records = sort(@records, cmp); for (record in @records) { emit1 record; } } '
color shape flag k index quantity rate yellow circle true 9 87 63.5058 8.3350 yellow circle true 8 73 63.9785 4.2370 red circle true 3 16 13.8103 2.9010 purple square false 10 91 72.3735 8.2430 red square false 6 64 77.1991 9.5310 red square false 4 48 77.5542 7.4670 red square true 2 15 79.2778 0.0130 purple triangle false 7 65 80.1405 5.8240 purple triangle false 5 51 81.2290 8.5910 yellow triangle true 1 11 43.6498 9.8870
Custom sorting of maps within records¶
Using the sort
function, you
can sort a map using a function which you specify (see the page on
user-defined functions) for comparing
keys and/or values.
- Your function must take four arguments, which will range over various pairs of key-value pairs in your map;
- It must return a number which is negative, zero, or positive depending on whether you want the first argument to sort less than, equal to, or greater than the second, respectively.
For example, we can sort ascending or descending by map key or map value:
mlr -n put -q ' func f1(ak, av, bk, bv) { return ak <=> bk } func f2(ak, av, bk, bv) { return bk <=> ak } func f3(ak, av, bk, bv) { return av <=> bv } func f4(ak, av, bk, bv) { return bv <=> av } end { x = { "c":1, "a":3, "b":2, }; print sort(x, f1); print sort(x, f2); print sort(x, f3); print sort(x, f4); } '
{ "a": 3, "b": 2, "c": 1 } { "c": 1, "b": 2, "a": 3 } { "c": 1, "b": 2, "a": 3 } { "a": 3, "b": 2, "c": 1 }
Custom sorting of maps across records¶
We can modify our above example just a bit, where we accumulate records in a map rather than
an array. Here the map keys will be NR
values "1"
, "2"
, etc.
Why would we do this? When we're operating across all records and keeping all
of them -- densely -- accumulating them in an array is fine. If we're only
taking a subset -- sparsely -- and we want to retain the original NR
as keys,
using a map is handy, since we don't need contiguous keys.
mlr --icsv --opprint --from example.csv put -q ' # Sort descending numeric on the index field func cmp(ak, av, bk, bv) { return bv.index <=> av.index } begin { @records = {}; # Define as a map } @records[NR] = $*; # Accumulate end { @records = sort(@records, cmp); for (_, record in @records) { emit1 record; } } '
color shape flag k index quantity rate purple square false 10 91 72.3735 8.2430 yellow circle true 9 87 63.5058 8.3350 yellow circle true 8 73 63.9785 4.2370 purple triangle false 7 65 80.1405 5.8240 red square false 6 64 77.1991 9.5310 purple triangle false 5 51 81.2290 8.5910 red square false 4 48 77.5542 7.4670 red circle true 3 16 13.8103 2.9010 red square true 2 15 79.2778 0.0130 yellow triangle true 1 11 43.6498 9.8870