Files
greptimedb/benchmarks/src/bin/nyc-taxi.rs
LFC 314f2704d4 build(deps): update datafusion to latest and arrow to 51.0 (#3661)
* chore: update datafusion

* update sqlness case of time.sql

Signed-off-by: Ruihang Xia <waynestxia@gmail.com>

* fix: adjust range query partition

* fix: hisogram incorrect result

Signed-off-by: Ruihang Xia <waynestxia@gmail.com>

* fix: ignore filter pushdown temporarily

Signed-off-by: Ruihang Xia <waynestxia@gmail.com>

* fix: update limit sqlness result

Signed-off-by: Ruihang Xia <waynestxia@gmail.com>

* fix: histogram with wrong distribution

Signed-off-by: Ruihang Xia <waynestxia@gmail.com>

* fix: update negative ordinal sqlness case

Signed-off-by: Ruihang Xia <waynestxia@gmail.com>

* feat: bump df to cd7a00b

Signed-off-by: Ruihang Xia <waynestxia@gmail.com>

* resolve conflicts

* ignore test_range_filter

Signed-off-by: Ruihang Xia <waynestxia@gmail.com>

* fix promql exec panic

* fix "select count(*)" exec error

* re-enable the "test_range_filter" test since the filter push down seems not necessary to be removed

* fix: range query schema error

* update sqlness results

Signed-off-by: Ruihang Xia <waynestxia@gmail.com>

* resolve conflicts

* update datafusion, again

* fix pyo3 compile error, and update some sqlness results

* update decimal sqlness cases

Signed-off-by: Ruihang Xia <waynestxia@gmail.com>

* fix: promql literal

* fix udaf tests

* fix filter pushdown sqlness tests

* fix?: test_cast

* fix: rspy test fail due to datafusion `sin` signature change

* rebase main to see if there are any failed tests

* debug ci

* debug ci

* debug ci

* enforce input partition

Signed-off-by: Ruihang Xia <waynestxia@gmail.com>

* debug ci

* fix ci

* fix ci

* debug ci

* debug ci

* debug ci

* fix sqlness

* feat: do not return error while creating a filter

* chore: remove array from error

* chore: replace todo with unimplemented

* Update src/flow/clippy.toml

Co-authored-by: Yingwen <realevenyag@gmail.com>

---------

Signed-off-by: Ruihang Xia <waynestxia@gmail.com>
Co-authored-by: Ruihang Xia <waynestxia@gmail.com>
Co-authored-by: WUJingdi <taylor-lagrange@qq.com>
Co-authored-by: discord9 <discord9@163.com>
Co-authored-by: evenyag <realevenyag@gmail.com>
Co-authored-by: tison <wander4096@gmail.com>
2024-04-18 12:07:18 +00:00

514 lines
18 KiB
Rust

// Copyright 2023 Greptime Team
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//! Use the taxi trip records from New York City dataset to bench. You can download the dataset from
//! [here](https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page).
#![allow(clippy::print_stdout)]
use std::collections::HashMap;
use std::path::{Path, PathBuf};
use std::time::Instant;
use arrow::array::{ArrayRef, PrimitiveArray, StringArray, TimestampMicrosecondArray};
use arrow::datatypes::{DataType, Float64Type, Int64Type};
use arrow::record_batch::RecordBatch;
use clap::Parser;
use client::api::v1::column::Values;
use client::api::v1::{
Column, ColumnDataType, ColumnDef, CreateTableExpr, InsertRequest, InsertRequests, SemanticType,
};
use client::{Client, Database, OutputData, DEFAULT_CATALOG_NAME, DEFAULT_SCHEMA_NAME};
use futures_util::TryStreamExt;
use indicatif::{MultiProgress, ProgressBar, ProgressStyle};
use parquet::arrow::arrow_reader::ParquetRecordBatchReaderBuilder;
use tokio::task::JoinSet;
const CATALOG_NAME: &str = "greptime";
const SCHEMA_NAME: &str = "public";
#[derive(Parser)]
#[command(name = "NYC benchmark runner")]
struct Args {
/// Path to the dataset
#[arg(short, long)]
path: Option<String>,
/// Batch size of insert request.
#[arg(short = 's', long = "batch-size", default_value_t = 4096)]
batch_size: usize,
/// Number of client threads on write (parallel on file level)
#[arg(short = 't', long = "thread-num", default_value_t = 4)]
thread_num: usize,
/// Number of query iteration
#[arg(short = 'i', long = "iter-num", default_value_t = 3)]
iter_num: usize,
#[arg(long = "skip-write")]
skip_write: bool,
#[arg(long = "skip-read")]
skip_read: bool,
#[arg(short, long, default_value_t = String::from("127.0.0.1:4001"))]
endpoint: String,
}
fn get_file_list<P: AsRef<Path>>(path: P) -> Vec<PathBuf> {
std::fs::read_dir(path)
.unwrap()
.map(|dir| dir.unwrap().path().canonicalize().unwrap())
.collect()
}
fn new_table_name() -> String {
format!("nyc_taxi_{}", chrono::Utc::now().timestamp())
}
async fn write_data(
table_name: &str,
batch_size: usize,
db: &Database,
path: PathBuf,
mpb: MultiProgress,
pb_style: ProgressStyle,
) -> u128 {
let file = std::fs::File::open(&path).unwrap();
let record_batch_reader_builder = ParquetRecordBatchReaderBuilder::try_new(file).unwrap();
let row_num = record_batch_reader_builder
.metadata()
.file_metadata()
.num_rows();
let record_batch_reader = record_batch_reader_builder
.with_batch_size(batch_size)
.build()
.unwrap();
let progress_bar = mpb.add(ProgressBar::new(row_num as _));
progress_bar.set_style(pb_style);
progress_bar.set_message(format!("{path:?}"));
let mut total_rpc_elapsed_ms = 0;
for record_batch in record_batch_reader {
let record_batch = record_batch.unwrap();
if !is_record_batch_full(&record_batch) {
continue;
}
let (columns, row_count) = convert_record_batch(record_batch);
let request = InsertRequest {
table_name: table_name.to_string(),
columns,
row_count,
};
let requests = InsertRequests {
inserts: vec![request],
};
let now = Instant::now();
db.insert(requests).await.unwrap();
let elapsed = now.elapsed();
total_rpc_elapsed_ms += elapsed.as_millis();
progress_bar.inc(row_count as _);
}
progress_bar.finish_with_message(format!("file {path:?} done in {total_rpc_elapsed_ms}ms",));
total_rpc_elapsed_ms
}
fn convert_record_batch(record_batch: RecordBatch) -> (Vec<Column>, u32) {
let schema = record_batch.schema();
let fields = schema.fields();
let row_count = record_batch.num_rows();
let mut columns = vec![];
for (array, field) in record_batch.columns().iter().zip(fields.iter()) {
let (values, datatype) = build_values(array);
let semantic_type = match field.name().as_str() {
"VendorID" => SemanticType::Tag,
"tpep_pickup_datetime" => SemanticType::Timestamp,
_ => SemanticType::Field,
};
let column = Column {
column_name: field.name().clone(),
values: Some(values),
null_mask: array
.to_data()
.nulls()
.map(|bitmap| bitmap.buffer().as_slice().to_vec())
.unwrap_or_default(),
datatype: datatype.into(),
semantic_type: semantic_type as i32,
..Default::default()
};
columns.push(column);
}
(columns, row_count as _)
}
fn build_values(column: &ArrayRef) -> (Values, ColumnDataType) {
match column.data_type() {
DataType::Int64 => {
let array = column
.as_any()
.downcast_ref::<PrimitiveArray<Int64Type>>()
.unwrap();
let values = array.values();
(
Values {
i64_values: values.to_vec(),
..Default::default()
},
ColumnDataType::Int64,
)
}
DataType::Float64 => {
let array = column
.as_any()
.downcast_ref::<PrimitiveArray<Float64Type>>()
.unwrap();
let values = array.values();
(
Values {
f64_values: values.to_vec(),
..Default::default()
},
ColumnDataType::Float64,
)
}
DataType::Timestamp(_, _) => {
let array = column
.as_any()
.downcast_ref::<TimestampMicrosecondArray>()
.unwrap();
let values = array.values();
(
Values {
timestamp_microsecond_values: values.to_vec(),
..Default::default()
},
ColumnDataType::TimestampMicrosecond,
)
}
DataType::Utf8 => {
let array = column.as_any().downcast_ref::<StringArray>().unwrap();
let values = array.iter().filter_map(|s| s.map(String::from)).collect();
(
Values {
string_values: values,
..Default::default()
},
ColumnDataType::String,
)
}
_ => unimplemented!(),
}
}
fn is_record_batch_full(batch: &RecordBatch) -> bool {
batch.columns().iter().all(|col| col.null_count() == 0)
}
fn create_table_expr(table_name: &str) -> CreateTableExpr {
CreateTableExpr {
catalog_name: CATALOG_NAME.to_string(),
schema_name: SCHEMA_NAME.to_string(),
table_name: table_name.to_string(),
desc: String::default(),
column_defs: vec![
ColumnDef {
name: "VendorID".to_string(),
data_type: ColumnDataType::Int64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Tag as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "tpep_pickup_datetime".to_string(),
data_type: ColumnDataType::TimestampMicrosecond as i32,
is_nullable: false,
default_constraint: vec![],
semantic_type: SemanticType::Timestamp as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "tpep_dropoff_datetime".to_string(),
data_type: ColumnDataType::TimestampMicrosecond as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "passenger_count".to_string(),
data_type: ColumnDataType::Float64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "trip_distance".to_string(),
data_type: ColumnDataType::Float64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "RatecodeID".to_string(),
data_type: ColumnDataType::Float64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "store_and_fwd_flag".to_string(),
data_type: ColumnDataType::String as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "PULocationID".to_string(),
data_type: ColumnDataType::Int64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "DOLocationID".to_string(),
data_type: ColumnDataType::Int64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "payment_type".to_string(),
data_type: ColumnDataType::Int64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "fare_amount".to_string(),
data_type: ColumnDataType::Float64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "extra".to_string(),
data_type: ColumnDataType::Float64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "mta_tax".to_string(),
data_type: ColumnDataType::Float64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "tip_amount".to_string(),
data_type: ColumnDataType::Float64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "tolls_amount".to_string(),
data_type: ColumnDataType::Float64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "improvement_surcharge".to_string(),
data_type: ColumnDataType::Float64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "total_amount".to_string(),
data_type: ColumnDataType::Float64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "congestion_surcharge".to_string(),
data_type: ColumnDataType::Float64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
ColumnDef {
name: "airport_fee".to_string(),
data_type: ColumnDataType::Float64 as i32,
is_nullable: true,
default_constraint: vec![],
semantic_type: SemanticType::Field as i32,
comment: String::new(),
..Default::default()
},
],
time_index: "tpep_pickup_datetime".to_string(),
primary_keys: vec!["VendorID".to_string()],
create_if_not_exists: true,
table_options: Default::default(),
table_id: None,
engine: "mito".to_string(),
}
}
fn query_set(table_name: &str) -> HashMap<String, String> {
HashMap::from([
(
"count_all".to_string(),
format!("SELECT COUNT(*) FROM {table_name};"),
),
(
"fare_amt_by_passenger".to_string(),
format!("SELECT passenger_count, MIN(fare_amount), MAX(fare_amount), SUM(fare_amount) FROM {table_name} GROUP BY passenger_count"),
)
])
}
async fn do_write(args: &Args, db: &Database, table_name: &str) {
let mut file_list = get_file_list(args.path.clone().expect("Specify data path in argument"));
let mut write_jobs = JoinSet::new();
let create_table_result = db.create(create_table_expr(table_name)).await;
println!("Create table result: {create_table_result:?}");
let progress_bar_style = ProgressStyle::with_template(
"[{elapsed_precise}] {bar:60.cyan/blue} {pos:>7}/{len:7} {msg}",
)
.unwrap()
.progress_chars("##-");
let multi_progress_bar = MultiProgress::new();
let file_progress = multi_progress_bar.add(ProgressBar::new(file_list.len() as _));
file_progress.inc(0);
let batch_size = args.batch_size;
for _ in 0..args.thread_num {
if let Some(path) = file_list.pop() {
let db = db.clone();
let mpb = multi_progress_bar.clone();
let pb_style = progress_bar_style.clone();
let table_name = table_name.to_string();
let _ = write_jobs.spawn(async move {
write_data(&table_name, batch_size, &db, path, mpb, pb_style).await
});
}
}
while write_jobs.join_next().await.is_some() {
file_progress.inc(1);
if let Some(path) = file_list.pop() {
let db = db.clone();
let mpb = multi_progress_bar.clone();
let pb_style = progress_bar_style.clone();
let table_name = table_name.to_string();
let _ = write_jobs.spawn(async move {
write_data(&table_name, batch_size, &db, path, mpb, pb_style).await
});
}
}
}
async fn do_query(num_iter: usize, db: &Database, table_name: &str) {
for (query_name, query) in query_set(table_name) {
println!("Running query: {query}");
for i in 0..num_iter {
let now = Instant::now();
let res = db.sql(&query).await.unwrap();
match res.data {
OutputData::AffectedRows(_) | OutputData::RecordBatches(_) => (),
OutputData::Stream(stream) => {
stream.try_collect::<Vec<_>>().await.unwrap();
}
}
let elapsed = now.elapsed();
println!(
"query {}, iteration {}: {}ms",
query_name,
i,
elapsed.as_millis(),
);
}
}
}
fn main() {
let args = Args::parse();
tokio::runtime::Builder::new_multi_thread()
.worker_threads(args.thread_num)
.enable_all()
.build()
.unwrap()
.block_on(async {
let client = Client::with_urls(vec![&args.endpoint]);
let db = Database::new(DEFAULT_CATALOG_NAME, DEFAULT_SCHEMA_NAME, client);
let table_name = new_table_name();
if !args.skip_write {
do_write(&args, &db, &table_name).await;
}
if !args.skip_read {
do_query(args.iter_num, &db, &table_name).await;
}
})
}