operator/req_convert/
common.rs

1// Copyright 2023 Greptime Team
2//
3// Licensed under the Apache License, Version 2.0 (the "License");
4// you may not use this file except in compliance with the License.
5// You may obtain a copy of the License at
6//
7//     http://www.apache.org/licenses/LICENSE-2.0
8//
9// Unless required by applicable law or agreed to in writing, software
10// distributed under the License is distributed on an "AS IS" BASIS,
11// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12// See the License for the specific language governing permissions and
13// limitations under the License.
14
15pub(crate) mod partitioner;
16
17use std::collections::HashMap;
18
19use api::helper::ColumnDataTypeWrapper;
20use api::v1::column_data_type_extension::TypeExt;
21use api::v1::column_def::options_from_column_schema;
22use api::v1::value::ValueData;
23use api::v1::{
24    Column, ColumnDataType, ColumnDataTypeExtension, ColumnSchema, JsonTypeExtension, Row,
25    RowDeleteRequest, RowInsertRequest, Rows, SemanticType, Value,
26};
27use common_base::BitVec;
28use datatypes::prelude::ConcreteDataType;
29use datatypes::vectors::VectorRef;
30use snafu::prelude::*;
31use snafu::ResultExt;
32use table::metadata::TableInfo;
33
34use crate::error::{
35    ColumnDataTypeSnafu, ColumnNotFoundSnafu, InvalidInsertRequestSnafu, InvalidJsonFormatSnafu,
36    MissingTimeIndexColumnSnafu, Result, UnexpectedSnafu,
37};
38
39/// Encodes a string value as JSONB binary data if the value is of `StringValue` type.
40fn encode_string_to_jsonb_binary(value_data: ValueData) -> Result<ValueData> {
41    if let ValueData::StringValue(json) = &value_data {
42        let binary = jsonb::parse_value(json.as_bytes())
43            .map_err(|_| InvalidJsonFormatSnafu { json }.build())
44            .map(|jsonb| jsonb.to_vec())?;
45        Ok(ValueData::BinaryValue(binary))
46    } else {
47        UnexpectedSnafu {
48            violated: "Expected to value data to be a string.",
49        }
50        .fail()
51    }
52}
53
54/// Prepares row insertion requests by converting any JSON values to binary JSONB format.
55pub fn preprocess_row_insert_requests(requests: &mut Vec<RowInsertRequest>) -> Result<()> {
56    for request in requests {
57        validate_rows(&request.rows)?;
58        prepare_rows(&mut request.rows)?;
59    }
60
61    Ok(())
62}
63
64/// Prepares row deletion requests by converting any JSON values to binary JSONB format.
65pub fn preprocess_row_delete_requests(requests: &mut Vec<RowDeleteRequest>) -> Result<()> {
66    for request in requests {
67        validate_rows(&request.rows)?;
68        prepare_rows(&mut request.rows)?;
69    }
70
71    Ok(())
72}
73
74fn prepare_rows(rows: &mut Option<Rows>) -> Result<()> {
75    if let Some(rows) = rows {
76        let indexes = rows
77            .schema
78            .iter()
79            .enumerate()
80            .filter_map(|(idx, schema)| {
81                if schema.datatype() == ColumnDataType::Json {
82                    Some(idx)
83                } else {
84                    None
85                }
86            })
87            .collect::<Vec<_>>();
88        for idx in &indexes {
89            let column = &mut rows.schema[*idx];
90            column.datatype_extension = Some(ColumnDataTypeExtension {
91                type_ext: Some(TypeExt::JsonType(JsonTypeExtension::JsonBinary.into())),
92            });
93            column.datatype = ColumnDataType::Json.into();
94        }
95
96        for idx in &indexes {
97            for row in &mut rows.rows {
98                if let Some(value_data) = row.values[*idx].value_data.take() {
99                    row.values[*idx].value_data = Some(encode_string_to_jsonb_binary(value_data)?);
100                }
101            }
102        }
103    }
104
105    Ok(())
106}
107
108fn validate_rows(rows: &Option<Rows>) -> Result<()> {
109    let Some(rows) = rows else {
110        return Ok(());
111    };
112
113    for (col_idx, schema) in rows.schema.iter().enumerate() {
114        let column_type =
115            ColumnDataTypeWrapper::try_new(schema.datatype, schema.datatype_extension)
116                .context(ColumnDataTypeSnafu)?
117                .into();
118
119        let ConcreteDataType::Vector(d) = column_type else {
120            return Ok(());
121        };
122
123        for row in &rows.rows {
124            let value = &row.values[col_idx].value_data;
125            if let Some(data) = value {
126                validate_vector_col(data, d.dim)?;
127            }
128        }
129    }
130
131    Ok(())
132}
133
134fn validate_vector_col(data: &ValueData, dim: u32) -> Result<()> {
135    let data = match data {
136        ValueData::BinaryValue(data) => data,
137        _ => {
138            return InvalidInsertRequestSnafu {
139                reason: "Expecting binary data for vector column.".to_string(),
140            }
141            .fail();
142        }
143    };
144
145    let expected_len = dim as usize * std::mem::size_of::<f32>();
146    if data.len() != expected_len {
147        return InvalidInsertRequestSnafu {
148            reason: format!(
149                "Expecting {} bytes of data for vector column, but got {}.",
150                expected_len,
151                data.len()
152            ),
153        }
154        .fail();
155    }
156
157    Ok(())
158}
159
160pub fn columns_to_rows(columns: Vec<Column>, row_count: u32) -> Result<Rows> {
161    let row_count = row_count as usize;
162    let column_count = columns.len();
163    let mut schema = Vec::with_capacity(column_count);
164    let mut rows = vec![
165        Row {
166            values: Vec::with_capacity(column_count)
167        };
168        row_count
169    ];
170    for column in columns {
171        let column_schema = ColumnSchema {
172            column_name: column.column_name.clone(),
173            datatype: column.datatype,
174            semantic_type: column.semantic_type,
175            datatype_extension: column.datatype_extension,
176            options: column.options.clone(),
177        };
178        schema.push(column_schema);
179
180        push_column_to_rows(column, &mut rows)?;
181    }
182
183    Ok(Rows { schema, rows })
184}
185
186fn push_column_to_rows(column: Column, rows: &mut [Row]) -> Result<()> {
187    let null_mask = BitVec::from_vec(column.null_mask);
188    let column_type = ColumnDataTypeWrapper::try_new(column.datatype, column.datatype_extension)
189        .context(ColumnDataTypeSnafu)?
190        .datatype();
191    let column_values = column.values.unwrap_or_default();
192
193    macro_rules! push_column_values_match_types {
194        ($( ($arm:tt, $value_data_variant:tt, $field_name:tt), )*) => { match column_type { $(
195
196        ColumnDataType::$arm => {
197            let row_count = rows.len();
198            let actual_row_count = null_mask.count_ones() + column_values.$field_name.len();
199            ensure!(
200                actual_row_count == row_count,
201                InvalidInsertRequestSnafu {
202                    reason: format!(
203                        "Expecting {} rows of data for column '{}', but got {}.",
204                        row_count, column.column_name, actual_row_count
205                    ),
206                }
207            );
208
209            let mut null_mask_iter = null_mask.into_iter();
210            let mut values_iter = column_values.$field_name.into_iter();
211
212            for row in rows {
213                let value_is_null = null_mask_iter.next();
214                if value_is_null == Some(true) {
215                    row.values.push(Value { value_data: None });
216                } else {
217                    // previous check ensures that there is a value for each row
218                    let value = values_iter.next().unwrap();
219                    row.values.push(Value {
220                        value_data: Some(ValueData::$value_data_variant(value)),
221                    });
222                }
223            }
224        }
225
226        )* }}
227    }
228
229    push_column_values_match_types!(
230        (Boolean, BoolValue, bool_values),
231        (Int8, I8Value, i8_values),
232        (Int16, I16Value, i16_values),
233        (Int32, I32Value, i32_values),
234        (Int64, I64Value, i64_values),
235        (Uint8, U8Value, u8_values),
236        (Uint16, U16Value, u16_values),
237        (Uint32, U32Value, u32_values),
238        (Uint64, U64Value, u64_values),
239        (Float32, F32Value, f32_values),
240        (Float64, F64Value, f64_values),
241        (Binary, BinaryValue, binary_values),
242        (String, StringValue, string_values),
243        (Json, StringValue, string_values),
244        (Date, DateValue, date_values),
245        (Datetime, DatetimeValue, datetime_values),
246        (
247            TimestampSecond,
248            TimestampSecondValue,
249            timestamp_second_values
250        ),
251        (
252            TimestampMillisecond,
253            TimestampMillisecondValue,
254            timestamp_millisecond_values
255        ),
256        (
257            TimestampMicrosecond,
258            TimestampMicrosecondValue,
259            timestamp_microsecond_values
260        ),
261        (
262            TimestampNanosecond,
263            TimestampNanosecondValue,
264            timestamp_nanosecond_values
265        ),
266        (TimeSecond, TimeSecondValue, time_second_values),
267        (
268            TimeMillisecond,
269            TimeMillisecondValue,
270            time_millisecond_values
271        ),
272        (
273            TimeMicrosecond,
274            TimeMicrosecondValue,
275            time_microsecond_values
276        ),
277        (TimeNanosecond, TimeNanosecondValue, time_nanosecond_values),
278        (
279            IntervalYearMonth,
280            IntervalYearMonthValue,
281            interval_year_month_values
282        ),
283        (
284            IntervalDayTime,
285            IntervalDayTimeValue,
286            interval_day_time_values
287        ),
288        (
289            IntervalMonthDayNano,
290            IntervalMonthDayNanoValue,
291            interval_month_day_nano_values
292        ),
293        (Decimal128, Decimal128Value, decimal128_values),
294        (Vector, BinaryValue, binary_values),
295    );
296
297    Ok(())
298}
299
300pub fn row_count(columns: &HashMap<String, VectorRef>) -> Result<usize> {
301    let mut columns_iter = columns.values();
302
303    let len = columns_iter
304        .next()
305        .map(|column| column.len())
306        .unwrap_or_default();
307    ensure!(
308        columns_iter.all(|column| column.len() == len),
309        InvalidInsertRequestSnafu {
310            reason: "The row count of columns is not the same."
311        }
312    );
313
314    Ok(len)
315}
316
317pub fn column_schema(
318    table_info: &TableInfo,
319    columns: &HashMap<String, VectorRef>,
320) -> Result<Vec<ColumnSchema>> {
321    columns
322        .iter()
323        .map(|(column_name, _vector)| {
324            let column_schema = table_info
325                .meta
326                .schema
327                .column_schema_by_name(column_name)
328                .context(ColumnNotFoundSnafu {
329                    msg: format!("unable to find column {column_name} in table schema"),
330                })?;
331
332            let (datatype, datatype_extension) =
333                ColumnDataTypeWrapper::try_from(column_schema.data_type.clone())
334                    .context(ColumnDataTypeSnafu)?
335                    .to_parts();
336
337            Ok(ColumnSchema {
338                column_name: column_name.clone(),
339                datatype: datatype as i32,
340                semantic_type: semantic_type(table_info, column_name)?.into(),
341                datatype_extension,
342                options: options_from_column_schema(column_schema),
343            })
344        })
345        .collect::<Result<Vec<_>>>()
346}
347
348fn semantic_type(table_info: &TableInfo, column: &str) -> Result<SemanticType> {
349    let table_meta = &table_info.meta;
350    let table_schema = &table_meta.schema;
351
352    let time_index_column = &table_schema
353        .timestamp_column()
354        .with_context(|| table::error::MissingTimeIndexColumnSnafu {
355            table_name: table_info.name.to_string(),
356        })
357        .context(MissingTimeIndexColumnSnafu)?
358        .name;
359
360    let semantic_type = if column == time_index_column {
361        SemanticType::Timestamp
362    } else {
363        let column_index = table_schema.column_index_by_name(column);
364        let column_index = column_index.context(ColumnNotFoundSnafu {
365            msg: format!("unable to find column {column} in table schema"),
366        })?;
367
368        if table_meta.primary_key_indices.contains(&column_index) {
369            SemanticType::Tag
370        } else {
371            SemanticType::Field
372        }
373    };
374
375    Ok(semantic_type)
376}
377
378#[cfg(test)]
379mod tests {
380    use api::v1::column::Values;
381    use api::v1::{SemanticType, VectorTypeExtension};
382    use common_base::bit_vec::prelude::*;
383
384    use super::*;
385
386    #[test]
387    fn test_request_column_to_row() {
388        let columns = vec![
389            Column {
390                column_name: String::from("col1"),
391                datatype: ColumnDataType::Int32.into(),
392                semantic_type: SemanticType::Field.into(),
393                null_mask: bitvec![u8, Lsb0; 1, 0, 1].into_vec(),
394                values: Some(Values {
395                    i32_values: vec![42],
396                    ..Default::default()
397                }),
398                ..Default::default()
399            },
400            Column {
401                column_name: String::from("col2"),
402                datatype: ColumnDataType::String.into(),
403                semantic_type: SemanticType::Tag.into(),
404                null_mask: vec![],
405                values: Some(Values {
406                    string_values: vec![
407                        String::from("value1"),
408                        String::from("value2"),
409                        String::from("value3"),
410                    ],
411                    ..Default::default()
412                }),
413                ..Default::default()
414            },
415            Column {
416                column_name: String::from("col3"),
417                datatype: ColumnDataType::Vector.into(),
418                semantic_type: SemanticType::Field.into(),
419                null_mask: vec![],
420                values: Some(Values {
421                    binary_values: vec![vec![0; 4], vec![1; 4], vec![2; 4]],
422                    ..Default::default()
423                }),
424                datatype_extension: Some(ColumnDataTypeExtension {
425                    type_ext: Some(TypeExt::VectorType(VectorTypeExtension { dim: 1 })),
426                }),
427                ..Default::default()
428            },
429        ];
430        let row_count = 3;
431
432        let result = columns_to_rows(columns, row_count);
433        let rows = result.unwrap();
434
435        assert_eq!(rows.schema.len(), 3);
436        assert_eq!(rows.schema[0].column_name, "col1");
437        assert_eq!(rows.schema[0].datatype, ColumnDataType::Int32 as i32);
438        assert_eq!(rows.schema[0].semantic_type, SemanticType::Field as i32);
439        assert_eq!(rows.schema[1].column_name, "col2");
440        assert_eq!(rows.schema[1].datatype, ColumnDataType::String as i32);
441        assert_eq!(rows.schema[1].semantic_type, SemanticType::Tag as i32);
442        assert_eq!(rows.schema[2].column_name, "col3");
443        assert_eq!(rows.schema[2].datatype, ColumnDataType::Vector as i32);
444        assert_eq!(rows.schema[2].semantic_type, SemanticType::Field as i32);
445        assert_eq!(
446            rows.schema[2].datatype_extension,
447            Some(ColumnDataTypeExtension {
448                type_ext: Some(TypeExt::VectorType(VectorTypeExtension { dim: 1 }))
449            })
450        );
451
452        assert_eq!(rows.rows.len(), 3);
453
454        assert_eq!(rows.rows[0].values.len(), 3);
455        assert_eq!(rows.rows[0].values[0].value_data, None);
456        assert_eq!(
457            rows.rows[0].values[1].value_data,
458            Some(ValueData::StringValue(String::from("value1")))
459        );
460        assert_eq!(
461            rows.rows[0].values[2].value_data,
462            Some(ValueData::BinaryValue(vec![0; 4]))
463        );
464
465        assert_eq!(rows.rows[1].values.len(), 3);
466        assert_eq!(
467            rows.rows[1].values[0].value_data,
468            Some(ValueData::I32Value(42))
469        );
470        assert_eq!(
471            rows.rows[1].values[1].value_data,
472            Some(ValueData::StringValue(String::from("value2")))
473        );
474        assert_eq!(
475            rows.rows[1].values[2].value_data,
476            Some(ValueData::BinaryValue(vec![1; 4]))
477        );
478
479        assert_eq!(rows.rows[2].values.len(), 3);
480        assert_eq!(rows.rows[2].values[0].value_data, None);
481        assert_eq!(
482            rows.rows[2].values[1].value_data,
483            Some(ValueData::StringValue(String::from("value3")))
484        );
485        assert_eq!(
486            rows.rows[2].values[2].value_data,
487            Some(ValueData::BinaryValue(vec![2; 4]))
488        );
489
490        // wrong type
491        let columns = vec![Column {
492            column_name: String::from("col1"),
493            datatype: ColumnDataType::Int32.into(),
494            semantic_type: SemanticType::Field.into(),
495            null_mask: bitvec![u8, Lsb0; 1, 0, 1].into_vec(),
496            values: Some(Values {
497                i8_values: vec![42],
498                ..Default::default()
499            }),
500            ..Default::default()
501        }];
502        let row_count = 3;
503        assert!(columns_to_rows(columns, row_count).is_err());
504
505        // wrong row count
506        let columns = vec![Column {
507            column_name: String::from("col1"),
508            datatype: ColumnDataType::Int32.into(),
509            semantic_type: SemanticType::Field.into(),
510            null_mask: bitvec![u8, Lsb0; 0, 0, 1].into_vec(),
511            values: Some(Values {
512                i32_values: vec![42],
513                ..Default::default()
514            }),
515            ..Default::default()
516        }];
517        let row_count = 3;
518        assert!(columns_to_rows(columns, row_count).is_err());
519
520        // wrong row count
521        let columns = vec![Column {
522            column_name: String::from("col1"),
523            datatype: ColumnDataType::Int32.into(),
524            semantic_type: SemanticType::Field.into(),
525            null_mask: vec![],
526            values: Some(Values {
527                i32_values: vec![42],
528                ..Default::default()
529            }),
530            ..Default::default()
531        }];
532        let row_count = 3;
533        assert!(columns_to_rows(columns, row_count).is_err());
534    }
535
536    #[test]
537    fn test_validate_vector_row_success() {
538        let data = ValueData::BinaryValue(vec![0; 4]);
539        let dim = 1;
540        assert!(validate_vector_col(&data, dim).is_ok());
541
542        let data = ValueData::BinaryValue(vec![0; 8]);
543        let dim = 2;
544        assert!(validate_vector_col(&data, dim).is_ok());
545
546        let data = ValueData::BinaryValue(vec![0; 12]);
547        let dim = 3;
548        assert!(validate_vector_col(&data, dim).is_ok());
549    }
550
551    #[test]
552    fn test_validate_vector_row_fail_wrong_type() {
553        let data = ValueData::I32Value(42);
554        let dim = 1;
555        assert!(validate_vector_col(&data, dim).is_err());
556    }
557
558    #[test]
559    fn test_validate_vector_row_fail_wrong_length() {
560        let data = ValueData::BinaryValue(vec![0; 8]);
561        let dim = 1;
562        assert!(validate_vector_col(&data, dim).is_err());
563
564        let data = ValueData::BinaryValue(vec![0; 4]);
565        let dim = 2;
566        assert!(validate_vector_col(&data, dim).is_err());
567    }
568}