use std::fs;
use std::io;
use channel;
use csv;
use stats::{merge_all, Frequencies};
use threadpool::ThreadPool;
use config::{Config, Delimiter};
use index::Indexed;
use select::{SelectColumns, Selection};
use util;
use CliResult;
static USAGE: &str = "
Compute a frequency table on CSV data.
The frequency table is formatted as CSV data:
field,value,count
By default, there is a row for the N most frequent values for each field in the
data. The order and number of values can be tweaked with --asc and --limit,
respectively.
Since this computes an exact frequency table, memory proportional to the
cardinality of each column is required.
Usage:
xan frequency [options] [<input>]
frequency options:
-s, --select <arg> Select a subset of columns to compute frequencies
for. See 'xan select --help' for the format
details. This is provided here because piping 'xan
select' into 'xan frequency' will disable the use
of indexing.
-l, --limit <arg> Limit the frequency table to the N most common
items. Set to <=0 to disable a limit. It is combined
with -t/--threshold.
[default: 10]
-t, --threshold <arg> If set, won't return items having a count less than
this given threshold. It is combined with -l/--limit.
-a, --asc Sort the frequency tables in ascending order by
count. The default is descending order.
-N, --no-extra Don't include null & remaining counts.
-j, --jobs <arg> The number of jobs to run in parallel.
This works better when the given CSV data has
an index already created. Note that a file handle
is opened for each job.
When set to '0', the number of jobs is set to the
number of CPUs detected.
[default: 0]
Common options:
-h, --help Display this message
-o, --output <file> Write output to <file> instead of stdout.
-n, --no-headers When set, the first row will NOT be included
in the frequency table. Additionally, the 'field'
column will be 1-based indices instead of header
names.
-d, --delimiter <arg> The field delimiter for reading CSV data.
Must be a single character. [default: ,]
";
#[derive(Clone, Deserialize)]
struct Args {
arg_input: Option<String>,
flag_select: SelectColumns,
flag_limit: usize,
flag_threshold: Option<u64>,
flag_asc: bool,
flag_no_extra: bool,
flag_jobs: usize,
flag_output: Option<String>,
flag_no_headers: bool,
flag_delimiter: Option<Delimiter>,
}
pub fn run(argv: &[&str]) -> CliResult<()> {
let args: Args = util::get_args(USAGE, argv)?;
let rconfig = args.rconfig();
let args_clone = args.clone();
let mut wtr = Config::new(&args.flag_output).writer()?;
let (headers, tables, row_count) = match args.rconfig().indexed()? {
Some(ref mut idx) if args.njobs() > 1 => args.parallel_ftables(idx),
_ => args.sequential_ftables(),
}?;
wtr.write_record(vec!["field", "value", "count"])?;
let head_ftables = headers.into_iter().zip(tables);
for (i, (header, ftab)) in head_ftables.enumerate() {
let header = if rconfig.no_headers {
(i + 1).to_string().into_bytes()
} else {
header.to_vec()
};
let mut seen_count: u64 = 0;
for (value, count) in args_clone.counts(&ftab).into_iter() {
seen_count += count;
let count = count.to_string();
let row = vec![&*header, &*value, count.as_bytes()];
wtr.write_record(row)?;
}
let remaining = row_count - seen_count;
if !args.flag_no_extra && remaining > 0 {
wtr.write_record(vec![&*header, b"<rest>", remaining.to_string().as_bytes()])?;
}
}
Ok(wtr.flush()?)
}
type ByteString = Vec<u8>;
type Headers = csv::ByteRecord;
type FTable = Frequencies<Vec<u8>>;
type FTables = Vec<Frequencies<Vec<u8>>>;
impl Args {
fn rconfig(&self) -> Config {
Config::new(&self.arg_input)
.delimiter(self.flag_delimiter)
.no_headers(self.flag_no_headers)
.select(self.flag_select.clone())
}
fn counts(&self, ftab: &FTable) -> Vec<(ByteString, u64)> {
let mut counts = if self.flag_asc {
ftab.least_frequent()
} else {
ftab.most_frequent()
};
if self.flag_limit > 0 {
counts = counts.into_iter().take(self.flag_limit).collect();
}
let counts = counts.into_iter().map(|(bs, c)| {
if b"" == &**bs {
(b"<null>".to_vec(), c)
} else {
(bs.clone(), c)
}
});
if let Some(t) = self.flag_threshold {
let counts = counts.filter(|(_, c)| *c >= t);
return counts.collect();
}
counts.collect()
}
fn sequential_ftables(&self) -> CliResult<(Headers, FTables, u64)> {
let mut rdr = self.rconfig().reader()?;
let (headers, sel) = self.sel_headers(&mut rdr)?;
let (ftables, count) = self.ftables(&sel, rdr.byte_records())?;
Ok((headers, ftables, count))
}
fn parallel_ftables(
&self,
idx: &mut Indexed<fs::File, fs::File>,
) -> CliResult<(Headers, FTables, u64)> {
let mut rdr = self.rconfig().reader()?;
let (headers, sel) = self.sel_headers(&mut rdr)?;
if idx.count() == 0 {
return Ok((headers, vec![], 0));
}
let chunk_size = util::chunk_size(idx.count() as usize, self.njobs());
let nchunks = util::num_of_chunks(idx.count() as usize, chunk_size);
let pool = ThreadPool::new(self.njobs());
let (send, recv) = channel::bounded(0);
for i in 0..nchunks {
let (send, args, sel) = (send.clone(), self.clone(), sel.clone());
pool.execute(move || {
let mut idx = args.rconfig().indexed().unwrap().unwrap();
idx.seek((i * chunk_size) as u64).unwrap();
let it = idx.byte_records().take(chunk_size);
let (ftable, _) = args.ftables(&sel, it).unwrap();
send.send(ftable);
});
}
drop(send);
Ok((headers, merge_all(recv).unwrap(), idx.count()))
}
fn ftables<I>(&self, sel: &Selection, it: I) -> CliResult<(FTables, u64)>
where
I: Iterator<Item = csv::Result<csv::ByteRecord>>,
{
let null = &b""[..].to_vec();
let nsel = sel.normal();
let mut tabs: Vec<_> = (0..nsel.len()).map(|_| Frequencies::new()).collect();
let mut count = 0;
for row in it {
let row = row?;
count += 1;
for (i, field) in nsel.select(row.into_iter()).enumerate() {
let field = field.to_vec();
if !field.is_empty() {
tabs[i].add(field);
} else if !self.flag_no_extra {
tabs[i].add(null.clone());
}
}
}
Ok((tabs, count))
}
fn sel_headers<R: io::Read>(
&self,
rdr: &mut csv::Reader<R>,
) -> CliResult<(csv::ByteRecord, Selection)> {
let headers = rdr.byte_headers()?;
let sel = self.rconfig().selection(headers)?;
Ok((sel.select(headers).map(|h| h.to_vec()).collect(), sel))
}
fn njobs(&self) -> usize {
if self.flag_jobs == 0 {
util::num_cpus()
} else {
self.flag_jobs
}
}
}