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Towards filling in more missing pieces

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This commit is contained in:
Dominik Werder
2021-05-04 18:24:30 +02:00
parent bf08893a98
commit be36dcce89
6 changed files with 73 additions and 66 deletions
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16
disk/src/agg/eventbatch.rs
View File

@@ -152,9 +152,6 @@ pub struct MinMaxAvgScalarEventBatchAggregator {
min: f32,
max: f32,
sum: f32,
event_data_read_stats: EventDataReadStats,
values_extract_stats: ValuesExtractStats,
range_complete_observed: bool,
}
impl MinMaxAvgScalarEventBatchAggregator {
@@ -166,9 +163,6 @@ impl MinMaxAvgScalarEventBatchAggregator {
max: f32::MIN,
sum: 0f32,
count: 0,
event_data_read_stats: EventDataReadStats::new(),
values_extract_stats: ValuesExtractStats::new(),
range_complete_observed: false,
}
}
}
@@ -209,11 +203,6 @@ impl AggregatorTdim for MinMaxAvgScalarEventBatchAggregator {
v.tss.last().map(|k| k / SEC),
);
}
self.event_data_read_stats.trans(&mut v.event_data_read_stats);
self.values_extract_stats.trans(&mut v.values_extract_stats);
if v.range_complete_observed {
self.range_complete_observed = true;
}
for i1 in 0..v.tss.len() {
let ts = v.tss[i1];
if ts < self.ts1 {
@@ -250,7 +239,7 @@ impl AggregatorTdim for MinMaxAvgScalarEventBatchAggregator {
}
}
fn result(mut self) -> Vec<Self::OutputValue> {
fn result(self) -> Vec<Self::OutputValue> {
let min = if self.min == f32::MAX { f32::NAN } else { self.min };
let max = if self.max == f32::MIN { f32::NAN } else { self.max };
let avg = if self.count == 0 {
@@ -265,9 +254,6 @@ impl AggregatorTdim for MinMaxAvgScalarEventBatchAggregator {
mins: vec![min],
maxs: vec![max],
avgs: vec![avg],
event_data_read_stats: std::mem::replace(&mut self.event_data_read_stats, EventDataReadStats::new()),
values_extract_stats: std::mem::replace(&mut self.values_extract_stats, ValuesExtractStats::new()),
range_complete_observed: self.range_complete_observed,
};
vec![v]
}

31
disk/src/agg/scalarbinbatch.rs
View File

@@ -1,8 +1,8 @@
use crate::agg::{AggregatableTdim, AggregatableXdim1Bin, AggregatorTdim, Fits, FitsInside, ValuesExtractStats};
use crate::agg::{AggregatableTdim, AggregatableXdim1Bin, AggregatorTdim, Fits, FitsInside};
use bytes::{BufMut, Bytes, BytesMut};
use netpod::log::*;
use netpod::timeunits::SEC;
use netpod::{EventDataReadStats, NanoRange};
use netpod::NanoRange;
use serde::{Deserialize, Serialize};
use std::mem::size_of;
@@ -15,9 +15,6 @@ pub struct MinMaxAvgScalarBinBatch {
pub mins: Vec<f32>,
pub maxs: Vec<f32>,
pub avgs: Vec<f32>,
pub event_data_read_stats: EventDataReadStats,
pub values_extract_stats: ValuesExtractStats,
pub range_complete_observed: bool,
}
impl MinMaxAvgScalarBinBatch {
@@ -29,9 +26,6 @@ impl MinMaxAvgScalarBinBatch {
mins: vec![],
maxs: vec![],
avgs: vec![],
event_data_read_stats: EventDataReadStats::new(),
values_extract_stats: ValuesExtractStats::new(),
range_complete_observed: false,
}
}
@@ -120,15 +114,12 @@ impl std::fmt::Debug for MinMaxAvgScalarBinBatch {
fn fmt(&self, fmt: &mut std::fmt::Formatter) -> std::fmt::Result {
write!(
fmt,
"MinMaxAvgScalarBinBatch count {} ts1s {:?} ts2s {:?} counts {:?} avgs {:?} EDS {:?} VXS {:?} COMP {}",
"MinMaxAvgScalarBinBatch count {} ts1s {:?} ts2s {:?} counts {:?} avgs {:?}",
self.ts1s.len(),
self.ts1s.iter().map(|k| k / SEC).collect::<Vec<_>>(),
self.ts2s.iter().map(|k| k / SEC).collect::<Vec<_>>(),
self.counts,
self.avgs,
self.event_data_read_stats,
self.values_extract_stats,
self.range_complete_observed,
)
}
}
@@ -210,9 +201,6 @@ pub struct MinMaxAvgScalarBinBatchAggregator {
max: f32,
sum: f32,
sumc: u64,
event_data_read_stats: EventDataReadStats,
values_extract_stats: ValuesExtractStats,
range_complete_observed: bool,
}
impl MinMaxAvgScalarBinBatchAggregator {
@@ -225,9 +213,6 @@ impl MinMaxAvgScalarBinBatchAggregator {
max: f32::MIN,
sum: 0f32,
sumc: 0,
event_data_read_stats: EventDataReadStats::new(),
values_extract_stats: ValuesExtractStats::new(),
range_complete_observed: false,
}
}
}
@@ -258,11 +243,6 @@ impl AggregatorTdim for MinMaxAvgScalarBinBatchAggregator {
}
fn ingest(&mut self, v: &mut Self::InputValue) {
self.event_data_read_stats.trans(&mut v.event_data_read_stats);
self.values_extract_stats.trans(&mut v.values_extract_stats);
if v.range_complete_observed {
self.range_complete_observed = true;
}
for i1 in 0..v.ts1s.len() {
let ts1 = v.ts1s[i1];
let ts2 = v.ts2s[i1];
@@ -280,7 +260,7 @@ impl AggregatorTdim for MinMaxAvgScalarBinBatchAggregator {
}
}
fn result(mut self) -> Vec<Self::OutputValue> {
fn result(self) -> Vec<Self::OutputValue> {
let min = if self.min == f32::MAX { f32::NAN } else { self.min };
let max = if self.max == f32::MIN { f32::NAN } else { self.max };
let avg = if self.sumc == 0 {
@@ -295,9 +275,6 @@ impl AggregatorTdim for MinMaxAvgScalarBinBatchAggregator {
mins: vec![min],
maxs: vec![max],
avgs: vec![avg],
event_data_read_stats: std::mem::replace(&mut self.event_data_read_stats, EventDataReadStats::new()),
values_extract_stats: std::mem::replace(&mut self.values_extract_stats, ValuesExtractStats::new()),
range_complete_observed: self.range_complete_observed,
};
vec![v]
}