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feat: don't map semantic type in metric engine (#3243)

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* feat: don't map semantic type in metric engine

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

* remove duplicate set_null

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

---------

Signed-off-by: Ruihang Xia <waynestxia@gmail.com>
This commit is contained in:
Ruihang Xia
2024-01-26 11:50:05 +08:00
committed by GitHub
parent 5617b284c5
commit b0c3be35fb
2 changed files with 3 additions and 17 deletions
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7
src/metric-engine/src/data_region.rs
View File

@@ -51,9 +51,9 @@ impl DataRegion {
/// Submit an alter request to underlying physical region.
///
/// This method will change the semantic type of those given columns.
/// [SemanticType::Tag] will become [SemanticType::Field]. The procedure framework
/// ensures there is no concurrent conflict.
/// This method will change the nullability of those given columns.
/// [SemanticType::Tag] will become nullable column as it's shared between
/// logical regions.
///
/// Invoker don't need to set up or verify the column id. This method will adjust
/// it using underlying schema.
@@ -124,7 +124,6 @@ impl DataRegion {
.map(|(delta, c)| {
let mut c = c.clone();
if c.semantic_type == SemanticType::Tag {
c.semantic_type = SemanticType::Field;
if !c.column_schema.data_type.is_string() {
return ColumnTypeMismatchSnafu {
column_type: c.column_schema.data_type,

13
src/metric-engine/src/engine/put.rs
View File

@@ -123,7 +123,6 @@ impl MetricEngineInner {
}
/// Perform metric engine specific logic to incoming rows.
/// - Change the semantic type of tag columns to field
/// - Add table_id column
/// - Generate tsid
fn modify_rows(&self, table_id: TableId, rows: &mut Rows) -> Result<()> {
@@ -141,18 +140,6 @@ impl MetricEngineInner {
})
.collect::<Vec<_>>();
// generate new schema
rows.schema = rows
.schema
.clone()
.into_iter()
.map(|mut col| {
if col.semantic_type == SemanticType::Tag as i32 {
col.semantic_type = SemanticType::Field as i32;
}
col
})
.collect::<Vec<_>>();
// add table_name column
rows.schema.push(ColumnSchema {
column_name: DATA_SCHEMA_TABLE_ID_COLUMN_NAME.to_string(),