datafusion-fiddle/api/main.rs at d8c7d74cb8ef6642c3bb313c584a308adaedf947 · datafusion-contrib/datafusion-fiddle · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
use arrow_flight::flight_service_server::FlightServiceServer;
use async_trait::async_trait;
use datafusion::arrow::error::ArrowError;
use datafusion::arrow::util::display::{ArrayFormatter, FormatOptions};
use datafusion::error::DataFusionError;
use datafusion::execution::SessionStateBuilder;
use datafusion::physical_plan::{displayable, execute_stream, ExecutionPlan};
use datafusion::prelude::{ParquetReadOptions, SessionConfig, SessionContext};
use datafusion_distributed::{
    display_plan_graphviz, ArrowFlightEndpoint, BoxCloneSyncChannel, ChannelResolver,
    DistributedExt, DistributedPhysicalOptimizerRule, DistributedSessionBuilderContext,
};
use futures::TryStreamExt;
use hyper_util::rt::TokioIo;
use serde::{Deserialize, Serialize};
use serde_json::json;
use std::env::current_dir;
use std::fmt::Display;
use std::fs;
use std::sync::{Arc, LazyLock};
use tonic::transport::{Endpoint, Server};
use vercel_runtime::{run, Body, Error, Request, RequestPayloadExt, Response, StatusCode};

const MAX_RESULTS: usize = 500;

const DUMMY_URL: &str = "http://localhost:50051";

#[derive(Clone)]
struct InMemoryChannelResolver {
    channel: BoxCloneSyncChannel,
}

impl InMemoryChannelResolver {
    fn new() -> Self {
        let (client, server) = tokio::io::duplex(1024 * 1024);

        let mut client = Some(client);
        let channel = Endpoint::try_from(DUMMY_URL)
            .expect("Invalid dummy URL for building an endpoint. This should never happen")
            .connect_with_connector_lazy(tower::service_fn(move |_| {
                let client = client
                    .take()
                    .expect("Client taken twice. This should never happen");
                async move { Ok::<_, std::io::Error>(TokioIo::new(client)) }
            }));

        let this = Self {
            channel: BoxCloneSyncChannel::new(channel),
        };
        let this_clone = this.clone();

        let endpoint =
            ArrowFlightEndpoint::try_new(move |ctx: DistributedSessionBuilderContext| {
                let this = this.clone();
                async move {
                    let builder = SessionStateBuilder::new()
                        .with_default_features()
                        .with_distributed_channel_resolver(this)
                        .with_runtime_env(ctx.runtime_env.clone());
                    Ok(builder.build())
                }
            })
            .unwrap();

        tokio::spawn(async move {
            Server::builder()
                .add_service(FlightServiceServer::new(endpoint))
                .serve_with_incoming(tokio_stream::once(Ok::<_, std::io::Error>(server)))
                .await
        });

        this_clone
    }
}

#[async_trait]
impl ChannelResolver for InMemoryChannelResolver {
    fn get_urls(&self) -> Result<Vec<url::Url>, DataFusionError> {
        Ok(vec![url::Url::parse(DUMMY_URL).unwrap()])
    }

    async fn get_channel_for_url(
        &self,
        _: &url::Url,
    ) -> Result<BoxCloneSyncChannel, DataFusionError> {
        Ok(self.channel.clone())
    }
}

static CHANNEL_RESOLVER: LazyLock<InMemoryChannelResolver> =
    LazyLock::new(InMemoryChannelResolver::new);

#[tokio::main]
async fn main() -> Result<(), Error> {
    run(handler).await
}

#[derive(Serialize, Deserialize, Default, Debug)]
struct SqlRequest {
    distributed: bool,
    stmts: Vec<String>,
    #[serde(default = "default_partitions")]
    partitions: usize,
    #[serde(default = "default_partitions_per_task")]
    partitions_per_task: usize,
}

fn default_partitions() -> usize {
    4
}

fn default_partitions_per_task() -> usize {
    2
}

pub async fn handler(req: Request) -> Result<Response<Body>, Error> {
    let req = match req.payload::<SqlRequest>()? {
        Some(req) => req,
        None => return throw_error("No sql request was passed", None, StatusCode::BAD_REQUEST),
    };

    let res = match execute_statements(
        req.stmts,
        "api/parquet",
        req.distributed,
        req.partitions,
        req.partitions_per_task,
    )
    .await
    {
        Ok(res) => res,
        Err(err) => {
            return throw_error(
                &err.to_string(),
                Some(Box::new(err)),
                StatusCode::BAD_REQUEST,
            )
        }
    };

    Ok(Response::builder()
        .status(StatusCode::OK)
        .header(
            "Cache-Control",
            format!(
                "public, max-age=0, must-revalidate, s-maxage={s_maxage}",
                s_maxage = 60 * 60
            ),
        )
        .header("Content-Type", "application/json")
        .body(json!(res).to_string().into())?)
}

pub fn throw_error(
    message: &str,
    error: Option<Error>,
    status_code: StatusCode,
) -> Result<Response<Body>, Error> {
    if let Some(error) = error {
        eprintln!("error: {error}");
    }

    Ok(Response::builder()
        .status(status_code)
        .header("Content-Type", "application/json")
        .body(json!({ "message": message }).to_string().into())?)
}

#[derive(Serialize, Deserialize, Default, Debug)]
struct SqlResult {
    columns: Vec<(String, String)>,
    rows: Vec<Vec<String>>,
    logical_plan: String,
    physical_plan: String,
    // if the plan is distributed, this contains the graphviz representation in dot format
    graphviz: String,
    // if the plan is distributed, this will be replaced browserside, with the svg html of the graphviz plan
    graphviz_plan: String,
}

async fn execute_statements(
    stmts: Vec<String>,
    path: impl Display,
    distributed: bool,
    partitions: usize,
    partitions_per_task: usize,
) -> datafusion::error::Result<SqlResult> {
    let options = FormatOptions::default().with_display_error(true);
    let mut cfg = SessionConfig::new()
        .with_information_schema(true)
        .with_target_partitions(partitions);

    let mut builder = SessionStateBuilder::new()
        .with_default_features()
        .with_config(cfg.clone());
    if distributed {
        cfg = cfg.set_str(
            "datafusion.optimizer.hash_join_single_partition_threshold",
            "0",
        );
        cfg = cfg.set_str(
            "datafusion.optimizer.hash_join_single_partition_threshold.rows",
            "0",
        );

        builder = builder
            .with_config(cfg)
            .with_physical_optimizer_rule(Arc::new(
                DistributedPhysicalOptimizerRule::default()
                    .with_maximum_partitions_per_task(partitions_per_task),
            ))
            .with_distributed_channel_resolver(CHANNEL_RESOLVER.clone());
    }
    let ctx = Arc::new(SessionContext::new_with_state(builder.build()));
    load_parquet_files(path.to_string(), &ctx).await?;

    if stmts.is_empty() {
        return Ok(SqlResult::default());
    }

    for i in 0..stmts.len() - 1 {
        ctx.sql(stmts.get(i).unwrap()).await?.collect().await?;
    }
    let df = ctx.sql(stmts.last().unwrap()).await?;
    let logical_plan_str = df.logical_plan().display_indent().to_string();

    let physical_plan = df.create_physical_plan().await?;

    let record_batches = execute_stream(physical_plan.clone(), ctx.task_ctx())?
        .try_collect::<Vec<_>>()
        .await?;

    let mut columns: Vec<(String, String)> = vec![];
    let mut rows: Vec<Vec<String>> = vec![];
    for record_batch in record_batches {
        if columns.is_empty() {
            columns = record_batch
                .schema()
                .fields
                .iter()
                .map(|e| (e.name().to_string(), e.data_type().to_string()))
                .collect()
        }

        let per_column_formatters = record_batch
            .columns()
            .iter()
            .map(|c| ArrayFormatter::try_new(c.as_ref(), &options))
            .collect::<Result<Vec<_>, ArrowError>>()?;

        for i in 0..record_batch.num_rows() {
            let mut row: Vec<String> = vec![];
            for formatter in &per_column_formatters {
                row.push(formatter.value(i).to_string());
            }
            rows.push(row);
        }
    }
    if rows.len() > MAX_RESULTS {
        rows.truncate(MAX_RESULTS);
        rows.push(vec!["...".to_string(); columns.len()]);
    }

    let physical_plan_str =
        display_physical_plan(&physical_plan).unwrap_or_else(|err| err.to_string());
    let graphviz_str = display_graphviz_plan(&physical_plan).unwrap_or_else(|err| err.to_string());

    Ok(SqlResult {
        columns,
        rows,
        logical_plan: logical_plan_str,
        physical_plan: physical_plan_str,
        graphviz_plan: "".to_owned(),
        graphviz: graphviz_str,
    })
}

fn display_physical_plan(physical_plan: &Arc<dyn ExecutionPlan>) -> Result<String, Error> {
    let physical_plan_str = displayable(physical_plan.as_ref()).indent(true).to_string();
    let curr_dir = current_dir()?.display().to_string();
    let curr_dir = curr_dir.trim_start_matches("/");
    let physical_plan_str = physical_plan_str.replace(curr_dir, "");
    Ok(physical_plan_str)
}

fn display_graphviz_plan(physical_plan: &Arc<dyn ExecutionPlan>) -> Result<String, Error> {
    let graphviz_plan_str = display_plan_graphviz(physical_plan.clone())?;
    Ok(graphviz_plan_str)
}

async fn load_parquet_files(base: String, ctx: &SessionContext) -> Result<(), DataFusionError> {
    let mut futures = vec![];
    for entry in fs::read_dir(&base)? {
        let entry_path = entry?.path();
        let file_name = entry_path.file_name().unwrap().display().to_string();
        let file_path = format!("{base}/{file_name}");

        let fut = ctx.register_parquet(file_name, file_path, ParquetReadOptions::default());
        futures.push(fut);
    }

    for result in futures::future::join_all(futures).await {
        result?
    }

    Ok(())
}

#[cfg(test)]
mod tests {
    use crate::{execute_statements, SqlResult};

    #[tokio::test]
    async fn test_create_table() -> datafusion::error::Result<()> {
        let result = execute_statements(
            vec![
                "CREATE TABLE book (str text)".to_string(),
                "INSERT INTO book (str) VALUES ('foo')".to_string(),
                "SELECT * FROM book".to_string(),
            ],
            format!("{}/api/parquet", env!("CARGO_MANIFEST_DIR")),
            false,
            4,
            2,
        )
        .await?;

        insta::assert_snapshot!(result, @r"
        +----------------+
        | str [Utf8View] |
        +----------------+
        | foo            |
        +----------------+
        ");
        Ok(())
    }

    #[tokio::test]
    async fn test_parquet() -> datafusion::error::Result<()> {
        let result = execute_statements(
            vec!["SELECT * FROM weather LIMIT 10".to_string()],
            format!("{}/api/parquet", env!("CARGO_MANIFEST_DIR")),
            false,
            4,
            2,
        )
        .await?;

        insta::assert_snapshot!(result, @r"
        +-------------------+-------------------+--------------------+-----------------------+---------------------+------------------------+--------------------------+-----------------------+-----------------------+-------------------------+----------------------+---------------------+---------------------+-----------------------+-----------------------+------------------+------------------+-------------------+-------------------+----------------------+-------------------+-------------------------+
        | MinTemp [Float64] | MaxTemp [Float64] | Rainfall [Float64] | Evaporation [Float64] | Sunshine [Utf8View] | WindGustDir [Utf8View] | WindGustSpeed [Utf8View] | WindDir9am [Utf8View] | WindDir3pm [Utf8View] | WindSpeed9am [Utf8View] | WindSpeed3pm [Int64] | Humidity9am [Int64] | Humidity3pm [Int64] | Pressure9am [Float64] | Pressure3pm [Float64] | Cloud9am [Int64] | Cloud3pm [Int64] | Temp9am [Float64] | Temp3pm [Float64] | RainToday [Utf8View] | RISK_MM [Float64] | RainTomorrow [Utf8View] |
        +-------------------+-------------------+--------------------+-----------------------+---------------------+------------------------+--------------------------+-----------------------+-----------------------+-------------------------+----------------------+---------------------+---------------------+-----------------------+-----------------------+------------------+------------------+-------------------+-------------------+----------------------+-------------------+-------------------------+
        | 8.0               | 24.3              | 0.0                | 3.4                   | 6.3                 | NW                     | 30                       | SW                    | NW                    | 6                       | 20                   | 68                  | 29                  | 1019.7                | 1015.0                | 7                | 7                | 14.4              | 23.6              | No                   | 3.6               | Yes                     |
        +-------------------+-------------------+--------------------+-----------------------+---------------------+------------------------+--------------------------+-----------------------+-----------------------+-------------------------+----------------------+---------------------+---------------------+-----------------------+-----------------------+------------------+------------------+-------------------+-------------------+----------------------+-------------------+-------------------------+
        | 14.0              | 26.9              | 3.6                | 4.4                   | 9.7                 | ENE                    | 39                       | E                     | W                     | 4                       | 17                   | 80                  | 36                  | 1012.4                | 1008.4                | 5                | 3                | 17.5              | 25.7              | Yes                  | 3.6               | Yes                     |
        +-------------------+-------------------+--------------------+-----------------------+---------------------+------------------------+--------------------------+-----------------------+-----------------------+-------------------------+----------------------+---------------------+---------------------+-----------------------+-----------------------+------------------+------------------+-------------------+-------------------+----------------------+-------------------+-------------------------+
        | 13.7              | 23.4              | 3.6                | 5.8                   | 3.3                 | NW                     | 85                       | N                     | NNE                   | 6                       | 6                    | 82                  | 69                  | 1009.5                | 1007.2                | 8                | 7                | 15.4              | 20.2              | Yes                  | 39.8              | Yes                     |
        +-------------------+-------------------+--------------------+-----------------------+---------------------+------------------------+--------------------------+-----------------------+-----------------------+-------------------------+----------------------+---------------------+---------------------+-----------------------+-----------------------+------------------+------------------+-------------------+-------------------+----------------------+-------------------+-------------------------+
        | 13.3              | 15.5              | 39.8               | 7.2                   | 9.1                 | NW                     | 54                       | WNW                   | W                     | 30                      | 24                   | 62                  | 56                  | 1005.5                | 1007.0                | 2                | 7                | 13.5              | 14.1              | Yes                  | 2.8               | Yes                     |
        +-------------------+-------------------+--------------------+-----------------------+---------------------+------------------------+--------------------------+-----------------------+-----------------------+-------------------------+----------------------+---------------------+---------------------+-----------------------+-----------------------+------------------+------------------+-------------------+-------------------+----------------------+-------------------+-------------------------+
        | 7.6               | 16.1              | 2.8                | 5.6                   | 10.6                | SSE                    | 50                       | SSE                   | ESE                   | 20                      | 28                   | 68                  | 49                  | 1018.3                | 1018.5                | 7                | 7                | 11.1              | 15.4              | Yes                  | 0.0               | No                      |
        +-------------------+-------------------+--------------------+-----------------------+---------------------+------------------------+--------------------------+-----------------------+-----------------------+-------------------------+----------------------+---------------------+---------------------+-----------------------+-----------------------+------------------+------------------+-------------------+-------------------+----------------------+-------------------+-------------------------+
        | 6.2               | 16.9              | 0.0                | 5.8                   | 8.2                 | SE                     | 44                       | SE                    | E                     | 20                      | 24                   | 70                  | 57                  | 1023.8                | 1021.7                | 7                | 5                | 10.9              | 14.8              | No                   | 0.2               | No                      |
        +-------------------+-------------------+--------------------+-----------------------+---------------------+------------------------+--------------------------+-----------------------+-----------------------+-------------------------+----------------------+---------------------+---------------------+-----------------------+-----------------------+------------------+------------------+-------------------+-------------------+----------------------+-------------------+-------------------------+
        | 6.1               | 18.2              | 0.2                | 4.2                   | 8.4                 | SE                     | 43                       | SE                    | ESE                   | 19                      | 26                   | 63                  | 47                  | 1024.6                | 1022.2                | 4                | 6                | 12.4              | 17.3              | No                   | 0.0               | No                      |
        +-------------------+-------------------+--------------------+-----------------------+---------------------+------------------------+--------------------------+-----------------------+-----------------------+-------------------------+----------------------+---------------------+---------------------+-----------------------+-----------------------+------------------+------------------+-------------------+-------------------+----------------------+-------------------+-------------------------+
        | 8.3               | 17.0              | 0.0                | 5.6                   | 4.6                 | E                      | 41                       | SE                    | E                     | 11                      | 24                   | 65                  | 57                  | 1026.2                | 1024.2                | 6                | 7                | 12.1              | 15.5              | No                   | 0.0               | No                      |
        +-------------------+-------------------+--------------------+-----------------------+---------------------+------------------------+--------------------------+-----------------------+-----------------------+-------------------------+----------------------+---------------------+---------------------+-----------------------+-----------------------+------------------+------------------+-------------------+-------------------+----------------------+-------------------+-------------------------+
        | 8.8               | 19.5              | 0.0                | 4.0                   | 4.1                 | S                      | 48                       | E                     | ENE                   | 19                      | 17                   | 70                  | 48                  | 1026.1                | 1022.7                | 7                | 7                | 14.1              | 18.9              | No                   | 16.2              | Yes                     |
        +-------------------+-------------------+--------------------+-----------------------+---------------------+------------------------+--------------------------+-----------------------+-----------------------+-------------------------+----------------------+---------------------+---------------------+-----------------------+-----------------------+------------------+------------------+-------------------+-------------------+----------------------+-------------------+-------------------------+
        | 8.4               | 22.8              | 16.2               | 5.4                   | 7.7                 | E                      | 31                       | S                     | ESE                   | 7                       | 6                    | 82                  | 32                  | 1024.1                | 1020.7                | 7                | 1                | 13.3              | 21.7              | Yes                  | 0.0               | No                      |
        +-------------------+-------------------+--------------------+-----------------------+---------------------+------------------------+--------------------------+-----------------------+-----------------------+-------------------------+----------------------+---------------------+---------------------+-----------------------+-----------------------+------------------+------------------+-------------------+-------------------+----------------------+-------------------+-------------------------+
        ");
        Ok(())
    }

    #[tokio::test]
    async fn test_distributed() -> datafusion::error::Result<()> {
        let result = execute_statements(
            // TPCH 17
            vec![r#"
select
        sum(l_extendedprice) / 7.0 as avg_yearly
from
    lineitem,
    part
where
        p_partkey = l_partkey
  and p_brand = 'Brand#23'
  and p_container = 'MED BOX'
  and l_quantity < (
    select
            0.2 * avg(l_quantity)
    from
        lineitem
    where
            l_partkey = p_partkey
);
            "#
            .to_string()],
            format!("{}/api/parquet", env!("CARGO_MANIFEST_DIR")),
            true,
            4,
            2,
        )
        .await?;

        insta::assert_snapshot!(result.physical_plan, @r"
        ┌───── Stage 2   Tasks: t0:[p0]
        │ ProjectionExec: expr=[CAST(sum(lineitem.l_extendedprice)@0 AS Float64) / 7 as avg_yearly]
        │   AggregateExec: mode=Final, gby=[], aggr=[sum(lineitem.l_extendedprice)]
        │     CoalescePartitionsExec
        │       AggregateExec: mode=Partial, gby=[], aggr=[sum(lineitem.l_extendedprice)]
        │         CoalesceBatchesExec: target_batch_size=8192
        │           HashJoinExec: mode=CollectLeft, join_type=Inner, on=[(p_partkey@2, l_partkey@1)], filter=CAST(l_quantity@0 AS Decimal128(30, 15)) < Float64(0.2) * avg(lineitem.l_quantity)@1, projection=[l_extendedprice@1]
        │             CoalescePartitionsExec
        │               ProjectionExec: expr=[l_quantity@1 as l_quantity, l_extendedprice@2 as l_extendedprice, p_partkey@0 as p_partkey]
        │                 CoalesceBatchesExec: target_batch_size=8192
        │                   HashJoinExec: mode=CollectLeft, join_type=Inner, on=[(p_partkey@0, l_partkey@0)], projection=[p_partkey@0, l_quantity@2, l_extendedprice@3]
        │                     CoalescePartitionsExec
        │                       CoalesceBatchesExec: target_batch_size=8192
        │                         FilterExec: p_brand@1 = Brand#23 AND p_container@2 = MED BOX, projection=[p_partkey@0]
        │                           DataSourceExec: file_groups={16 groups: [[/api/parquet/part/1.parquet], [/api/parquet/part/10.parquet], [/api/parquet/part/11.parquet], [/api/parquet/part/12.parquet], [/api/parquet/part/13.parquet], ...]}, projection=[p_partkey, p_brand, p_container], file_type=parquet, predicate=p_brand@1 = Brand#23 AND p_container@2 = MED BOX, pruning_predicate=p_brand_null_count@2 != row_count@3 AND p_brand_min@0 <= Brand#23 AND Brand#23 <= p_brand_max@1 AND p_container_null_count@6 != row_count@3 AND p_container_min@4 <= MED BOX AND MED BOX <= p_container_max@5, required_guarantees=[p_brand in (Brand#23), p_container in (MED BOX)]
        │                     DataSourceExec: file_groups={16 groups: [[/api/parquet/lineitem/1.parquet], [/api/parquet/lineitem/10.parquet], [/api/parquet/lineitem/11.parquet], [/api/parquet/lineitem/12.parquet], [/api/parquet/lineitem/13.parquet], ...]}, projection=[l_partkey, l_quantity, l_extendedprice], file_type=parquet
        │             ProjectionExec: expr=[CAST(0.2 * CAST(avg(lineitem.l_quantity)@1 AS Float64) AS Decimal128(30, 15)) as Float64(0.2) * avg(lineitem.l_quantity), l_partkey@0 as l_partkey]
        │               AggregateExec: mode=FinalPartitioned, gby=[l_partkey@0 as l_partkey], aggr=[avg(lineitem.l_quantity)]
        │                 CoalesceBatchesExec: target_batch_size=8192
        │                   ArrowFlightReadExec input_stage=1, input_partitions=16, input_tasks=16
        └──────────────────────────────────────────────────
          ┌───── Stage 1   Tasks: t0:[p0] t1:[p1] t2:[p2] t3:[p3] t4:[p4] t5:[p5] t6:[p6] t7:[p7] t8:[p8] t9:[p9] t10:[p10] t11:[p11] t12:[p12] t13:[p13] t14:[p14] t15:[p15]
          │ RepartitionExec: partitioning=Hash([l_partkey@0], 16), input_partitions=1
          │   PartitionIsolatorExec Tasks: t0:[p0,__,__,__,__,__,__,__,__,__,__,__,__,__,__,__] t1:[__,p0,__,__,__,__,__,__,__,__,__,__,__,__,__,__] t2:[__,__,p0,__,__,__,__,__,__,__,__,__,__,__,__,__] t3:[__,__,__,p0,__,__,__,__,__,__,__,__,__,__,__,__] t4:[__,__,__,__,p0,__,__,__,__,__,__,__,__,__,__,__] t5:[__,__,__,__,__,p0,__,__,__,__,__,__,__,__,__,__] t6:[__,__,__,__,__,__,p0,__,__,__,__,__,__,__,__,__] t7:[__,__,__,__,__,__,__,p0,__,__,__,__,__,__,__,__] t8:[__,__,__,__,__,__,__,__,p0,__,__,__,__,__,__,__] t9:[__,__,__,__,__,__,__,__,__,p0,__,__,__,__,__,__] t10:[__,__,__,__,__,__,__,__,__,__,p0,__,__,__,__,__] t11:[__,__,__,__,__,__,__,__,__,__,__,p0,__,__,__,__] t12:[__,__,__,__,__,__,__,__,__,__,__,__,p0,__,__,__] t13:[__,__,__,__,__,__,__,__,__,__,__,__,__,p0,__,__] t14:[__,__,__,__,__,__,__,__,__,__,__,__,__,__,p0,__] t15:[__,__,__,__,__,__,__,__,__,__,__,__,__,__,__,p0]
          │     AggregateExec: mode=Partial, gby=[l_partkey@0 as l_partkey], aggr=[avg(lineitem.l_quantity)]
          │       DataSourceExec: file_groups={16 groups: [[/api/parquet/lineitem/1.parquet], [/api/parquet/lineitem/10.parquet], [/api/parquet/lineitem/11.parquet], [/api/parquet/lineitem/12.parquet], [/api/parquet/lineitem/13.parquet], ...]}, projection=[l_partkey, l_quantity], file_type=parquet
          └──────────────────────────────────────────────────
        ");
        Ok(())
    }

    impl std::fmt::Display for SqlResult {
        fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
            let mut builder = tabled::builder::Builder::new();
            for (i, (name, typ)) in self.columns.iter().enumerate() {
                let values = self
                    .rows
                    .iter()
                    .map(|v| v.get(i).unwrap())
                    .collect::<Vec<_>>();
                builder.push_column([vec![&format!("{name} [{typ}]")], values].concat())
            }
            let table = builder.build();
            write!(f, "{}", table)
        }
    }
}