recs-collate
Help from: --help-aggregators: array: collect values from provided field into an array average, avg: averages provided field cb, countby: counts by unique value for a field concat, concatenate: concatenate values from provided field corr, correl, correlation: find correlation of provided fields count, ct: counts (non-unique) records cov, covar, covariance: find covariance of provided fields dcount, dct, distinctcount, distinctct: count unique values from provided field first: first value for a field firstrec, firstrecord: first record last: last value for a field lastrec, lastrecord: last record seen linearregression, linreg: perform a linear regression of provided fields, dumping various statistics max, maximum: maximum value for a field min, minimum: minimum value for a field mode: most common value for a field perc, percentile: value of pXX for field percentilemap, percmap: map of percentile values for field recformax, recformaximum, recordformax, recordformaximum: returns the record corresponding to the maximum value for a field recformin, recforminimum, recordformin, recordforminimum: returns the record corresponding to the minimum value for a field records, recs: returns an arrayref of all records stddev: find standard deviation of provided field sum: sums provided field uarray: collect unique values from provided field into an array uconcat, uconcatenate: concatenate unique values from provided field valuestokeys, vk: use one key-value as a key for a different value in the record var, variance: find variance of provided field Help from: --help-basic: Usage: recs-collate <args> [<files>] Take records, grouped togther by --keys, and compute statistics (like average, count, sum, concat, etc) within those groups. For starting with collate, try doing single --key collates with some number of aggregators (list available in --list-agrregators) Arguments: --dlaggregator|-A ... Specify a domain language aggregate. See "Domain Language Integration" below. --aggregator|-a <aggregators> Colon separated list of aggregate field specifiers. See "Aggregates" section below. --mr-agg <name> <map> <reduce> <squish> Specify a map reduce aggregator via 3 snippets, similar to mr_agg() from the domain language. --ii-agg <name> <initial> <combine> <squish> Specify an inject into aggregator via 3 snippets, similar to ii_agg() from the domain language. --incremental Output a record every time an input record is added to a clump (instead of every time a clump is flushed). --[no]-bucket With --bucket outputs one record per clump, with --no- bucket outputs one record for each record that went into the clump. --key|-k <keys> Comma separated list of key fields. May be a key spec or key group --dlkey|-K ... Specify a domain language key. See "Domain Language Integration" section in --help- more. --size|--sz|-n <number> Number of running clumps to keep. --adjacent|-1 Only group together adjacent records. Avoids spooling records into memeory --cube See "Cubing" section in --help- more. --clumper ... Use this clumper to group records. May be specified multiple times. See --help- clumping. --dlclumper ... Use this domain language clumper to group records. May be specified multiple times. See --help-clumping. --list-aggregators|--list Bail and output a list of aggregators --show-aggregator <aggregator> Bail and output this aggregator's detailed usage. --list-clumpers Bail and output a list of clumpers --show-clumper <clumper> Bail and output this clumper's detailed usage. --filename-key|fk <keyspec> Add a key with the source filename (if no filename is applicable will put NONE) Help Options: --help-aggregators List the aggregators --help-all Output all help for this script --help This help screen --help-clumping Help on clumping; mechanisms to group records across a stream --help-domainlanguage Help on the recs domain language, a [very complicated] way of specifying valuations (which act like keys) or aggregators --help-keygroups Help on keygroups, a way of specifying multiple keys --help-keys Help on keygroups and keyspecs --help-keyspecs Help on keyspecs, a way to index deeply and with regexes --help-more Larger help documentation Examples: Count clumps of adjacent lines with matching x fields. recs-collate --adjacent --key x --aggregator count Count number of each x field value in the entire file. recs-collate --key x --aggregator count Finds the maximum latency for each date, hour pair recs-collate --key date,hour --aggregator worst_latency=max,latency Find the median value of x+y in records recs-collate --dlaggregator "m=perc(50,snip(<<{{x}}+{{y}}>>))" Help from: --help-clumping: CLUMPING: "Clumping" defines a way of taking a stream of input records and rearranging them into to groups for consideration. The most common "consideration" for such a group of records is the application of one or more aggregators by recs- collate and the most common clumpers are those specifiable by recs-collate's normal options. However, other recs scripts can use "clumpers" and much more complex clumping is possible. A list of clumpers can be found via the --list- clumpers option on recs-collate and documentation for individual clumpers can be inspected via --show-clumper. Examples: Group adjacent records for each host and output each such group's size. recs-collate -c keylru,host,1 -a ct Output the successive differences of the time field. recs-collate -c window,2 --dla 'time_delta=xform(recs, <<{{#1/time}} - {{#0/time}}>>)' Full list: cubekeyperfect: clump records by the value for a key, additionally cubing them keylru: clump records by the value for a key, limiting number of active clumps keyperfect: clump records by the value for a key window: clump records by a rolling window Help from: --help-domainlanguage: DOMAIN LANGUAGE The normal mechanism for specifying keys and aggregators allows one to concisely instantiate the objects that back them in the platform and is certainly the easiest way to use recs. The record stream domain language allows the creation of these objects in a programmatic way, with neither the syntactic issues of the normal way nor its guiding hand. The domain language is itself just Perl with a collection of library functions for creating platform objects included. Your favorite aggregators are all here with constructors matching their normal token. For convenience of e.g. last, aggregators are also included with a prefixed underscore. Below you can find documentation on all the "built in" functions. Most aggregators and deaggregators should be present with arguments comparable to their normal instantiation arugments, but with keyspec parameters replaced with valuations parameters. Special Syntax Where one sees a <snippet> argument below, a string scalar is expected, however quoting these can get fairly difficult and they can be confused with non-<snippet> scalars. Example: --dla "silly= uconcat(',', snip('{{x}} * 2'))" To remedy this, one may use <<CODE>> to inline a snippet which will be immediately understood by the typing mechanism as being code. Escaping inside this is as single quotes in Perl. Example With <<CODE>> --dla 'silly= uconcat(",", <<{{x}} * 2>>)' Furthermore one may mark variables to be propagated in by prefixing CODE like <<var1,var2,var3|CODE>>: --dla 'silly= $f=2; uconcat(",", <<f|{{x}} * $f>>)' Function Library ii_agg(<snippet>, <snippet>[, <snippet>]) ii_aggregator(<snippet>, <snippet>[, <snippet>]) inject_into_agg(<snippet>, <snippet>[, <snippet>]) inject_into_aggregator(<snippet>, <snippet>[, <snippet>]) Take an initial snippet, a combine snippet, and an optional squish snippet to produce an ad-hoc aggregator based on inject into. The initial snippet produces the aggregate value for an empty collection, then combine takes $a representing the aggregate value so far and $r representing the next record to add and returns the new aggregate value. Finally, the squish snippet takes $a representing the final aggregate value so far and produces the final answer for the aggregator. Example(s): Track count and sum to produce average: ii_agg(<<[0, 0]>>, <<[$a->[0] + 1, $a->[1] + {{ct}}]>>, <<$a->[1] / $a->[0]>>) for_field(qr/.../, <snippet>) Takes a regex and a snippet of code. Creates an aggregator that creates a map. Keys in the map correspond to fields chosen by matching the regex against the fields from input records. Values in the map are produced by aggregators which the snippet must act as a factory for ($f is the field). Example(s): To aggregate the sums of all the fields beginning with "t" for_field(qr/^t/, <<sum($f)>>) for_field(qr/.../, qr/.../, <snippet>) Takes two regexes and a snippet of code. Creates an aggregator that creates a map. Keys in the map correspond to pairs of fields chosen by matching the regexes against the fields from input records. Values in the map are produced by aggregators which the snippet must act as a factory for ($f1 is the first field, $f2 is the second field). Example(s): To find the covariance of all x-named fields with all y-named fields: for_field(qr/^x/, qr/^y/, <<covar($f1, $f2)>>) map_reduce_agg(<snippet>, <snippet>[, <snippet>]) map_reduce_aggregator(<snippet>, <snippet>[, <snippet>]) mr_agg(<snippet>, <snippet>[, <snippet>]) mr_aggregator(<snippet>, <snippet>[, <snippet>]) Take a map snippet, a reduce snippet, and an optional squish snippet to produce an ad-hoc aggregator based on map reduce. The map snippet takes $r representing a record and returns its mapped value. The reduce snippet takes $a and $b representing two mapped values and combines them. Finally, the squish snippet takes a mapped value $a representing all the records and produces the final answer for the aggregator. Example(s): Track count and sum to produce average: mr_agg(<<[1, {{ct}}]>>, <<[$a->[0] + $b->[0], $a->[1] + $b->[1]]>>, <<$a->[1] / $a->[0]>>) rec() record() A valuation that just returns the entire record. snip(snip) Takes a snippet and returns both the snippet and the snippet as a valuation. Used to distinguished snippets from scalars in cases where it matters, e.g. min('{{x}}') interprets it is a keyspec when it was meant to be a snippet (and then a valuation), min(snip('{{x}}')) does what is intended. This is used internally by <<...>> and in fact <<...>> just translates to snip('...'). subset_agg(<snippet>, <aggregator>) subset_aggregator(<snippet>, <aggregator>) Takes a snippate to act as a record predicate and an aggregator and produces an aggregator that acts as the provided aggregator as run on the filtered view. Example(s): An aggregator that counts the number of records with a time not above 6 seconds: subset_agg(<<{{time_ms}} <= 6000>>, ct()) type_agg(obj) type_scalar(obj) type_val(obj) Force the object into a specific type. Can be used to force certain upconversions (or avoid them). valuation(sub { ... }) val(sub { ... }) Takes a subref, creates a valuation that represents it. The subref will get the record as its first and only argument. Example(s): To get the square of the "x" field: val(sub{ $[0]->{x} ** 2 }) xform(<aggregator>, <snippet>) Takes an aggregator and a snippet and produces an aggregator the represents invoking the snippet on the aggregator's result. Example(s): To take the difference between the first and second time fields of the record collection: xform(recs(), <<{{1/time}} - {{0/time}}>>) Help from: --help-keygroups: KEY GROUPS SYNTAX: !regex!opt1!opt2... Key groups are a way of specifying multiple fields to a recs command with a single argument or function. They are generally regexes, and have several options to control what fields they match. By default you give a regex, and it will be matched against all first level keys of a record to come up with the record list. For instance, in a record like this: { 'zip': 1, 'zap': 2, 'foo': { 'bar': 3 } } Key group: !z! would get the keys 'zip' and 'zap' You can have a literal '!' in your regex, just escape it with a \. Normally, key groups will only match keys whose values are scalars. This can be changed with the 'returnrefs' or rr flag. With the above record !f! would match no fields, but !f!rr would match foo (which has a value of a hash ref) Options on KeyGroups: returnrefs, rr - Return keys that have reference values (default:off) full, f - Regex should match against full keys (recurse fully) depth=NUM,d=NUM - Only match keys at NUM depth (regex will match against full keyspec) sort, s - sort keyspecs lexically Help from: --help-keyspecs: KEY SPECS A key spec is short way of specifying a field with prefixes or regular expressions, it may also be nested into hashes and arrays. Use a '/' to nest into a hash and a '#NUM' to index into an array (i.e. #2) An example is in order, take a record like this: {"biz":["a","b","c"],"foo":{"bar 1":1},"zap":"blah1"} {"biz":["a","b","c"],"foo":{"bar 1":2},"zap":"blah2"} {"biz":["a","b","c"],"foo":{"bar 1":3},"zap":"blah3"} In this case a key spec of 'foo/bar 1' would have the values 1,2, and 3 in the respective records. Similarly, 'biz/#0' would have the value of 'a' for all 3 records You can also prefix key specs with '@' to engage the fuzzy matching logic Fuzzy matching works like this in order, first key to match wins 1. Exact match ( eq ) 2. Prefix match ( m/^/ ) 3. Match anywehre in the key (m//) So, in the above example '@b/#2', the 'b' portion would expand to 'biz' and 2 would be the index into the array, so all records would have the value of 'c' Simiarly, @f/b would have values 1, 2, and 3 You can escape / with a \. For example, if you have a record: {"foo/bar":2} You can address that key with foo\/bar Help from: --help-more: Usage: recs-collate <args> [<files>] Take records, grouped togther by --keys, and compute statistics (like average, count, sum, concat, etc) within those groups. For starting with collate, try doing single --key collates with some number of aggregators (list available in --list-agrregators) Arguments: --dlaggregator|-A ... Specify a domain language aggregate. See "Domain Language Integration" below. --aggregator|-a <aggregators> Colon separated list of aggregate field specifiers. See "Aggregates" section below. --mr-agg <name> <map> <reduce> <squish> Specify a map reduce aggregator via 3 snippets, similar to mr_agg() from the domain language. --ii-agg <name> <initial> <combine> <squish> Specify an inject into aggregator via 3 snippets, similar to ii_agg() from the domain language. --incremental Output a record every time an input record is added to a clump (instead of every time a clump is flushed). --[no]-bucket With --bucket outputs one record per clump, with --no- bucket outputs one record for each record that went into the clump. --key|-k <keys> Comma separated list of key fields. May be a key spec or key group --dlkey|-K ... Specify a domain language key. See "Domain Language Integration" section in --help- more. --size|--sz|-n <number> Number of running clumps to keep. --adjacent|-1 Only group together adjacent records. Avoids spooling records into memeory --cube See "Cubing" section in --help- more. --clumper ... Use this clumper to group records. May be specified multiple times. See --help- clumping. --dlclumper ... Use this domain language clumper to group records. May be specified multiple times. See --help-clumping. --list-aggregators|--list Bail and output a list of aggregators --show-aggregator <aggregator> Bail and output this aggregator's detailed usage. --list-clumpers Bail and output a list of clumpers --show-clumper <clumper> Bail and output this clumper's detailed usage. --filename-key|fk <keyspec> Add a key with the source filename (if no filename is applicable will put NONE) Help Options: --help-aggregators List the aggregators --help-all Output all help for this script --help This help screen --help-clumping Help on clumping; mechanisms to group records across a stream --help-domainlanguage Help on the recs domain language, a [very complicated] way of specifying valuations (which act like keys) or aggregators --help-keygroups Help on keygroups, a way of specifying multiple keys --help-keys Help on keygroups and keyspecs --help-keyspecs Help on keyspecs, a way to index deeply and with regexes --help-more Larger help documentation Examples: Count clumps of adjacent lines with matching x fields. recs-collate --adjacent --key x --aggregator count Count number of each x field value in the entire file. recs-collate --key x --aggregator count Finds the maximum latency for each date, hour pair recs-collate --key date,hour --aggregator worst_latency=max,latency Find the median value of x+y in records recs-collate --dlaggregator "m=perc(50,snip(<<{{x}}+{{y}}>>))" Aggregates: Aggregates are specified as [<fieldname>=]<aggregator>[,<arguments>]. The default field name is aggregator and arguments joined by underscores. See --list- aggregators for a list of available aggregators. Fieldname maybe a key spec. (i.e. foo/bar=sum,field). Additionally, all key name arguments to aggregators maybe be key specs (i.e. foo=max,latency/url), but not key groups Cubing: Instead of added one entry for each input record, we add 2 ** (number of key fields), with every possible combination of fields replaced with the default of "ALL". This is not meant to be used with --adjacent or --size. If our key fields were x and y then we'd get output records for {x = 1, y = 2}, {x = 1, y = ALL}, {x = ALL, y = 2} and {x = ALL, y = ALL}. Domain Lanuage Integration: The normal mechanism for specifying keys and aggregators allows one to concisely instantiate the objects that back them in the platform and is certainly the easiest way to use recs. The record stream domain language allows the creation of these objects in a programmatic way, with neither the syntactic issues of the normal way nor its guiding hand. The domain language is itself just Perl with a collection of library functions for creating platform objects included. Your favorite aggregators are all here with constructors matching their normal token. For convenience of e.g. last, aggregators are also included with a prefixed underscore. Below you can find documentation on all the "built in" functions. Most aggregators and deaggregators should be present with arguments comparable to their normal instantiation arugments, but with keyspec parameters replaced with valuations parameters. Either aggregates or keys may be specified using the recs domain language. Both --dlkey and --dlaggregator require an options of the format '<name>=<domain language code>'. --dlkey requires the code evaluate as a valuation, --dlaggregator requires the code evaluate as an aggregator. See --help-domainlanguage for a more complete description of its workings and a list of available functions. See the examples below for a more gentle introduction. Examples: Count clumps of adjacent lines with matching x fields. recs-collate --adjacent --key x --aggregator count Count number of each x field in the entire file. recs-collate --key x --aggregator count Count number of each x field in the entire file, including an "ALL" line. recs-collate --key x --aggregator count --cube Produce a cummulative sum of field profit up to each date recs-collate --key date --adjacent --incremental --aggregator profit_to_date=sum,profit Produce record count for each date, hour pair recs-collate --key date,hour --aggregator count Finds the maximum latency for each date, hour pair recs-collate --key date,hour --aggregator worst_latency=max,latency Produce a list of hosts in each datacenter. recs-collate --key dc --dlaggregator "hosts=uconcat(', ', 'host')" Sum all time fields recs-collate --key ... --dlaggregator 'times=for_field(qr/^t/, <<sum($f)>>)' Find the median value of x+y in records recs-collate --dlaggregator "m=perc(50,snip(<<{{x}}+{{y}}>>))" Count people by first three letters of their name recs-collate --dlkey "tla=<<substr({{name}},0,3)>>" -a ct
See App::RecordStream for an overview of the scripts and the system
Run recs examples or see App::RecordStream::Manual::Examples for a set of simple recs examples
recs examples
Run recs story or see App::RecordStream::Manual::Story for a humorous introduction to RecordStream
recs story
Every command has a --help mode available to print out usage and examples for the particular command, just like the output above.
--help
To install App::RecordStream, copy and paste the appropriate command in to your terminal.
cpanm
cpanm App::RecordStream
CPAN shell
perl -MCPAN -e shell install App::RecordStream
For more information on module installation, please visit the detailed CPAN module installation guide.