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refactor: simplification of static schema handling #1192

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refactor: simplification of static schema handling #1192

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1561742
refactor: simplification of static schema handling
de-sh Feb 16, 2025
dc09121
refactor: custom error type
de-sh Feb 18, 2025
53ac33f
style: clippy suggestion
de-sh Feb 18, 2025
f864c0e
perf iterate less
de-sh Feb 18, 2025
7616d47
put it in quotes
de-sh Feb 18, 2025
3cee271
refactor: directly construct `Field`
de-sh Feb 18, 2025
7f2ee9a
style: type names
de-sh Feb 18, 2025
71202ef
refactor: simplify flow with a map
de-sh Feb 18, 2025
5149831
Merge branch 'main' into static-schema
de-sh Feb 18, 2025
509d8d6
Merge branch 'main' into static-schema
de-sh Feb 18, 2025
3e9bb84
Merge remote-tracking branch 'origin/main' into static-schema
de-sh Mar 4, 2025
d6ca844
Merge remote-tracking branch 'origin/main' into static-schema
de-sh Mar 14, 2025
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62 changes: 23 additions & 39 deletions src/parseable/mod.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,7 @@ use crate::{
},
metadata::{LogStreamMetadata, SchemaVersion},
option::Mode,
static_schema::{convert_static_schema_to_arrow_schema, StaticSchema},
static_schema::StaticSchema,
storage::{
object_storage::parseable_json_path, ObjectStorageError, ObjectStorageProvider,
ObjectStoreFormat, Owner, Permisssion, StreamType,
Expand Down Expand Up @@ -485,13 +485,28 @@ impl Parseable {
}
}

let schema = validate_static_schema(
body,
stream_name,
&time_partition,
custom_partition.as_ref(),
static_schema_flag,
)?;
let schema = if static_schema_flag {
if body.is_empty() {
return Err(CreateStreamError::Custom {
msg: format!(
"Please provide schema in the request body for static schema logstream {stream_name}"
),
status: StatusCode::BAD_REQUEST,
}.into());
}

let static_schema: StaticSchema = serde_json::from_slice(body)?;
static_schema
.convert_to_arrow_schema(&time_partition, custom_partition.as_ref())
.map_err(|_| CreateStreamError::Custom {
msg: format!(
"Unable to commit static schema, logstream {stream_name} not created"
),
status: StatusCode::BAD_REQUEST,
})?
} else {
Arc::new(Schema::empty())
};

self.create_stream(
stream_name.to_string(),
Expand Down Expand Up @@ -778,37 +793,6 @@ impl Parseable {
}
}

pub fn validate_static_schema(
body: &Bytes,
stream_name: &str,
time_partition: &str,
custom_partition: Option<&String>,
static_schema_flag: bool,
) -> Result<Arc<Schema>, CreateStreamError> {
if !static_schema_flag {
return Ok(Arc::new(Schema::empty()));
}

if body.is_empty() {
return Err(CreateStreamError::Custom {
msg: format!(
"Please provide schema in the request body for static schema logstream {stream_name}"
),
status: StatusCode::BAD_REQUEST,
});
}

let static_schema: StaticSchema = serde_json::from_slice(body)?;
let parsed_schema =
convert_static_schema_to_arrow_schema(static_schema, time_partition, custom_partition)
.map_err(|_| CreateStreamError::Custom {
msg: format!("Unable to commit static schema, logstream {stream_name} not created"),
status: StatusCode::BAD_REQUEST,
})?;

Ok(parsed_schema)
}

pub fn validate_time_partition_limit(
time_partition_limit: &str,
) -> Result<NonZeroU32, CreateStreamError> {
Expand Down
205 changes: 88 additions & 117 deletions src/static_schema.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -29,19 +29,100 @@ pub struct StaticSchema {
fields: Vec<SchemaFields>,
}

impl StaticSchema {
pub fn convert_to_arrow_schema(
self,
time_partition: &str,
custom_partition: Option<&String>,
) -> Result<Arc<Schema>, AnyError> {
let mut fields = Vec::new();
let mut time_partition_exists = false;

if let Some(custom_partition) = custom_partition {
for partition in custom_partition.split(',') {
if !self.fields.iter().any(|field| field.name == partition) {
return Err(anyhow!("custom partition field {partition} does not exist in the schema for the static schema logstream"));
}
}
}
for mut field in self.fields {
if !time_partition.is_empty() && field.name == time_partition {
time_partition_exists = true;
field.data_type = "datetime".to_string();
}

let parsed_field = Fields {
name: field.name.clone(),

data_type: {
match field.data_type.as_str() {
"int" => DataType::Int64,
"double" | "float" => DataType::Float64,
"boolean" => DataType::Boolean,
"string" => DataType::Utf8,
"datetime" => DataType::Timestamp(TimeUnit::Millisecond, None),
"string_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Utf8, true)))
}
"int_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Int64, true)))
}
"double_list" | "float_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Float64, true)))
}
"boolean_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Boolean, true)))
}
_ => DataType::Null,
}
},
nullable: default_nullable(),
dict_id: default_dict_id(),
dict_is_ordered: default_dict_is_ordered(),
metadata: HashMap::new(),
};

fields.push(parsed_field);
}
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🛠️ Refactor suggestion

Return an explicit error for unrecognized data types instead of defaulting to null.

Falling back to DataType::Null for unknown types can silently mask typos or misunderstandings in the schema. Consider returning an error to highlight the invalid type rather than converting it to null.

- _ => DataType::Null,
+ other => {
+     return Err(anyhow!("Unsupported or unrecognized data type: {other}"));
+ }
📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
let parsed_field = Fields {
name: field.name.clone(),
data_type: {
match field.data_type.as_str() {
"int" => DataType::Int64,
"double" | "float" => DataType::Float64,
"boolean" => DataType::Boolean,
"string" => DataType::Utf8,
"datetime" => DataType::Timestamp(TimeUnit::Millisecond, None),
"string_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Utf8, true)))
}
"int_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Int64, true)))
}
"double_list" | "float_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Float64, true)))
}
"boolean_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Boolean, true)))
}
_ => DataType::Null,
}
},
nullable: default_nullable(),
dict_id: default_dict_id(),
dict_is_ordered: default_dict_is_ordered(),
metadata: HashMap::new(),
};
fields.push(parsed_field);
}
let parsed_field = Fields {
name: field.name.clone(),
data_type: {
match field.data_type.as_str() {
"int" => DataType::Int64,
"double" | "float" => DataType::Float64,
"boolean" => DataType::Boolean,
"string" => DataType::Utf8,
"datetime" => DataType::Timestamp(TimeUnit::Millisecond, None),
"string_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Utf8, true)))
}
"int_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Int64, true)))
}
"double_list" | "float_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Float64, true)))
}
"boolean_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Boolean, true)))
}
other => {
return Err(anyhow!("Unsupported or unrecognized data type: {other}"));
}
}
},
nullable: default_nullable(),
dict_id: default_dict_id(),
dict_is_ordered: default_dict_is_ordered(),
metadata: HashMap::new(),
};
fields.push(parsed_field);


if !time_partition.is_empty() && !time_partition_exists {
return Err(anyhow!("time partition field {time_partition} does not exist in the schema for the static schema logstream"));
}

let mut schema: Vec<Arc<Field>> = Vec::new();
for field in fields {
let field = Field::new(field.name.clone(), field.data_type.clone(), field.nullable);
schema.push(Arc::new(field));
}

if get_field(&schema, DEFAULT_TIMESTAMP_KEY).is_some() {
return Err(anyhow!(
"field {} is a reserved field",
DEFAULT_TIMESTAMP_KEY
));
};

// add the p_timestamp field to the event schema to the 0th index
schema.insert(
0,
Arc::new(Field::new(
DEFAULT_TIMESTAMP_KEY,
DataType::Timestamp(TimeUnit::Millisecond, None),
true,
)),
);

// prepare the record batch and new fields to be added
Ok(Arc::new(Schema::new(schema)))
}
}

#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct SchemaFields {
name: String,
data_type: String,
}

#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
#[serde(rename_all = "camelCase")]
pub struct ParsedSchema {
pub fields: Vec<Fields>,
pub metadata: HashMap<String, String>,
}

#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
#[serde(rename_all = "camelCase")]
pub struct Fields {
Expand All @@ -56,116 +137,6 @@ pub struct Fields {
#[derive(Default, Debug, Clone, PartialEq, Serialize, Deserialize)]

pub struct Metadata {}
pub fn convert_static_schema_to_arrow_schema(
static_schema: StaticSchema,
time_partition: &str,
custom_partition: Option<&String>,
) -> Result<Arc<Schema>, AnyError> {
let mut parsed_schema = ParsedSchema {
fields: Vec::new(),
metadata: HashMap::new(),
};
let mut time_partition_exists = false;

if let Some(custom_partition) = custom_partition {
let custom_partition_list = custom_partition.split(',').collect::<Vec<&str>>();
let mut custom_partition_exists = HashMap::with_capacity(custom_partition_list.len());

for partition in &custom_partition_list {
if static_schema
.fields
.iter()
.any(|field| &field.name == partition)
{
custom_partition_exists.insert(partition.to_string(), true);
}
}

for partition in &custom_partition_list {
if !custom_partition_exists.contains_key(*partition) {
return Err(anyhow!("custom partition field {partition} does not exist in the schema for the static schema logstream"));
}
}
}
for mut field in static_schema.fields {
if !time_partition.is_empty() && field.name == time_partition {
time_partition_exists = true;
field.data_type = "datetime".to_string();
}

let parsed_field = Fields {
name: field.name.clone(),

data_type: {
match field.data_type.as_str() {
"int" => DataType::Int64,
"double" | "float" => DataType::Float64,
"boolean" => DataType::Boolean,
"string" => DataType::Utf8,
"datetime" => DataType::Timestamp(TimeUnit::Millisecond, None),
"string_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Utf8, true)))
}
"int_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Int64, true)))
}
"double_list" | "float_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Float64, true)))
}
"boolean_list" => {
DataType::List(Arc::new(Field::new("item", DataType::Boolean, true)))
}
_ => DataType::Null,
}
},
nullable: default_nullable(),
dict_id: default_dict_id(),
dict_is_ordered: default_dict_is_ordered(),
metadata: HashMap::new(),
};

parsed_schema.fields.push(parsed_field);
}
if !time_partition.is_empty() && !time_partition_exists {
return Err(anyhow! {
format!(
"time partition field {time_partition} does not exist in the schema for the static schema logstream"
),
});
}
add_parseable_fields_to_static_schema(parsed_schema)
}

fn add_parseable_fields_to_static_schema(
parsed_schema: ParsedSchema,
) -> Result<Arc<Schema>, AnyError> {
let mut schema: Vec<Arc<Field>> = Vec::new();
for field in parsed_schema.fields.iter() {
let field = Field::new(field.name.clone(), field.data_type.clone(), field.nullable);
schema.push(Arc::new(field));
}

if get_field(&schema, DEFAULT_TIMESTAMP_KEY).is_some() {
return Err(anyhow!(
"field {} is a reserved field",
DEFAULT_TIMESTAMP_KEY
));
};

// add the p_timestamp field to the event schema to the 0th index
schema.insert(
0,
Arc::new(Field::new(
DEFAULT_TIMESTAMP_KEY,
DataType::Timestamp(TimeUnit::Millisecond, None),
true,
)),
);

// prepare the record batch and new fields to be added
let schema = Arc::new(Schema::new(schema));
Ok(schema)
}

fn default_nullable() -> bool {
true
Expand Down
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