Refactor product creator, remove threading for writing to disk

This commit is contained in:
piv
2023-03-11 10:55:41 +10:30
parent 363c972b71
commit 7cd893cbf8
5 changed files with 250 additions and 256 deletions

View File

@@ -0,0 +1,139 @@
use core::panic;
use std::{
collections::HashMap,
io::{Read, Write},
sync::mpsc,
thread,
};
use chrono::NaiveDateTime;
use csv::Position;
use serde::Serialize;
use super::csv::{read_definitions, BuildFrom, ConstraintType, Definition};
#[derive(Debug, Serialize, Default)]
struct Product {
// Parse datetime from string: https://rust-lang-nursery.github.io/rust-cookbook/datetime/parse.html#parse-string-into-datetime-struct
// TODO: Serialisers.
start_date_time: NaiveDateTime,
end_date_time: NaiveDateTime,
encounter_start_date_time: Option<NaiveDateTime>,
encounter: Option<String>,
service: Option<String>,
transfer: Option<String>,
quantity: Option<f64>,
duration: Option<f64>,
actual_charge: Option<f64>,
standard_cost: Option<f64>,
// TODO: Enum this?
day_of_stay: Option<u8>,
source_allocated_amount: Option<f64>,
}
// TODO: Build from linked dataset is pretty hard, it potentially requires knowing everything abuot the previous year's
// cosing run (BSCO, Dataset_Encounter_Cache, etc).
pub fn create_products<D, E, S, T, P, Di, O>(
definitions: &mut csv::Reader<D>,
encounters: &mut csv::Reader<E>,
services: &mut csv::Reader<S>,
transfers: &mut csv::Reader<T>,
procedures: &mut csv::Reader<P>,
diagnoses: &mut csv::Reader<Di>,
// TODO: Looks kind of bad, any other way around it? I'd rather not have to depend on crossbeam as well
output: &mut csv::Writer<O>,
// TODO: Default to 10 million or something sane
batch_size: usize,
) -> anyhow::Result<()>
where
D: Read,
E: Read,
S: Read,
T: Read,
P: Read,
Di: Read,
// TODO: Looks kind of bad, any other way around it? I'd rather not have to depend on crossbeam as well
O: Write + Send + 'static,
{
let mut all_definitions: HashMap<String, Definition> = read_definitions(definitions)?;
// Partition the rules by the build from type, so that we'll run all the rules at once for a particular file, which should be much faster
// then opening files and scanning one at a time. Could also do batches in files
let mut mapped_definitions: HashMap<BuildFrom, Vec<Definition>> = HashMap::new();
for (_, definition) in all_definitions {
mapped_definitions
.entry(definition.build_from)
.or_insert(vec![])
.push(definition);
}
// Now whenever we want to produce a built service, just write it to tx.
// Note that rust csv can seek to a certain position, so we can read in a batch from a reader, then
// seek to that position in the reader (or position 0) if we couldn't find a particular record.
// Alternatively, we could store an index of all records (e.g. encounter numbers) that map to their position in the reader,
// so we can quickly seek to the appropriate index and read the record.
// https://docs.rs/csv/latest/csv/struct.Reader.html#method.seek
// Store encounter positions in file, so that later when we read through transfers/whatever we can easily
// seak to the correct position quickly in case we have a cache miss
let mut encounter_positions: HashMap<String, Position> = HashMap::new();
// TODO: Alternative to storing encounter positions would be to sort portions of the file bits at a time (I think it's called a merge sort?).
// TODO: Try with and without rayon, should be able to help I think as we're going through so much data sequentially,
// although we're still likely to be bottlenecked by just write-speed
let mut encounters = encounters;
let headers = encounters.headers()?.clone();
for encounter in encounters.records() {
let encounter = encounter?;
let position = encounter.position().unwrap();
let encounter: HashMap<String, String> = encounter.deserialize(Some(&headers))?;
encounter_positions.insert(
encounter.get("EncounterNumber").unwrap().to_string(),
position.clone(),
);
// TODO: For each encounter definition, check this fits the filter criteria/constraints,
// and
let definitions = mapped_definitions.get(&BuildFrom::Encounter).unwrap();
for definition in definitions {
let matching_filter = (definition.filters.is_empty()
|| definition.filters.iter().any(|filter| {
let field = encounter.get(filter.field.as_str());
if field.is_none() {
return false;
}
let field = field.unwrap();
if filter.equal {
return filter.value == *field;
} else {
return filter.value != *field;
}
}))
&& (definition.constraints.is_empty()
|| definition.constraints.iter().any(|constraint| {
let field = encounter.get(constraint.field.as_str());
if field.is_none() {
return false;
}
let field = field.unwrap();
// TODO: Is this just number/datetime? Should probably be an enum? It's not, seems to be E in the test data
let field_type = &constraint.source_type;
match constraint.constraint_type {
ConstraintType::Equal => *field == constraint.value,
_ => false,
}
}));
if matching_filter {
// Generate the service code
}
}
// TODO: Generate the built service
output.serialize(Product::default());
}
// Now do the same with transfers, services, etc, referencing the encounter reader by using the
// indexes in encounter_positions
Ok(())
}