Replace custom serialization with a saner version

The Materialized View code had custom serialization written so we could
move this code forward. Now that we have many operators and the views
work, replace it with something saner.

The main insight is that if we transform the AggregateState into Values
before the serialization, we are able to just use standard SQLite
serialization for the values. We then just have to add sizes, codes for
the functions, etc (which are also represented as Values).
This commit is contained in:
Glauber Costa
2025-09-25 07:13:31 -03:00
parent 3113822ceb
commit b9011dfa16
4 changed files with 473 additions and 323 deletions

View File

@@ -16,6 +16,13 @@ use std::sync::{Arc, Mutex};
pub const AGG_TYPE_REGULAR: u8 = 0b00; // COUNT/SUM/AVG
pub const AGG_TYPE_MINMAX: u8 = 0b01; // MIN/MAX (BTree ordering gives both)
// Serialization type codes for aggregate functions
const AGG_FUNC_COUNT: i64 = 0;
const AGG_FUNC_SUM: i64 = 1;
const AGG_FUNC_AVG: i64 = 2;
const AGG_FUNC_MIN: i64 = 3;
const AGG_FUNC_MAX: i64 = 4;
#[derive(Debug, Clone, PartialEq)]
pub enum AggregateFunction {
Count,
@@ -44,6 +51,104 @@ impl AggregateFunction {
self.to_string()
}
/// Serialize this aggregate function to a Value
/// Returns a vector of values: [type_code, optional_column_index]
pub fn to_values(&self) -> Vec<Value> {
match self {
AggregateFunction::Count => vec![Value::Integer(AGG_FUNC_COUNT)],
AggregateFunction::Sum(idx) => {
vec![Value::Integer(AGG_FUNC_SUM), Value::Integer(*idx as i64)]
}
AggregateFunction::Avg(idx) => {
vec![Value::Integer(AGG_FUNC_AVG), Value::Integer(*idx as i64)]
}
AggregateFunction::Min(idx) => {
vec![Value::Integer(AGG_FUNC_MIN), Value::Integer(*idx as i64)]
}
AggregateFunction::Max(idx) => {
vec![Value::Integer(AGG_FUNC_MAX), Value::Integer(*idx as i64)]
}
}
}
/// Deserialize an aggregate function from values
/// Consumes values from the cursor and returns the aggregate function
pub fn from_values(values: &[Value], cursor: &mut usize) -> Result<Self> {
let type_code = values
.get(*cursor)
.ok_or_else(|| LimboError::InternalError("Missing aggregate type code".into()))?;
let agg_fn = match type_code {
Value::Integer(AGG_FUNC_COUNT) => {
*cursor += 1;
AggregateFunction::Count
}
Value::Integer(AGG_FUNC_SUM) => {
*cursor += 1;
let idx = values
.get(*cursor)
.ok_or_else(|| LimboError::InternalError("Missing SUM column index".into()))?;
if let Value::Integer(idx) = idx {
*cursor += 1;
AggregateFunction::Sum(*idx as usize)
} else {
return Err(LimboError::InternalError(format!(
"Expected Integer for SUM column index, got {idx:?}"
)));
}
}
Value::Integer(AGG_FUNC_AVG) => {
*cursor += 1;
let idx = values
.get(*cursor)
.ok_or_else(|| LimboError::InternalError("Missing AVG column index".into()))?;
if let Value::Integer(idx) = idx {
*cursor += 1;
AggregateFunction::Avg(*idx as usize)
} else {
return Err(LimboError::InternalError(format!(
"Expected Integer for AVG column index, got {idx:?}"
)));
}
}
Value::Integer(AGG_FUNC_MIN) => {
*cursor += 1;
let idx = values
.get(*cursor)
.ok_or_else(|| LimboError::InternalError("Missing MIN column index".into()))?;
if let Value::Integer(idx) = idx {
*cursor += 1;
AggregateFunction::Min(*idx as usize)
} else {
return Err(LimboError::InternalError(format!(
"Expected Integer for MIN column index, got {idx:?}"
)));
}
}
Value::Integer(AGG_FUNC_MAX) => {
*cursor += 1;
let idx = values
.get(*cursor)
.ok_or_else(|| LimboError::InternalError("Missing MAX column index".into()))?;
if let Value::Integer(idx) = idx {
*cursor += 1;
AggregateFunction::Max(*idx as usize)
} else {
return Err(LimboError::InternalError(format!(
"Expected Integer for MAX column index, got {idx:?}"
)));
}
}
_ => {
return Err(LimboError::InternalError(format!(
"Unknown aggregate type code: {type_code:?}"
)))
}
};
Ok(agg_fn)
}
/// Create an AggregateFunction from a SQL function and its arguments
/// Returns None if the function is not a supported aggregate
pub fn from_sql_function(
@@ -77,42 +182,6 @@ pub struct AggColumnInfo {
pub has_max: bool,
}
/// Serialize a Value using SQLite's serial type format
/// This is used for MIN/MAX values that need to be stored in a compact, sortable format
pub fn serialize_value(value: &Value, blob: &mut Vec<u8>) {
let serial_type = crate::types::SerialType::from(value);
let serial_type_u64: u64 = serial_type.into();
crate::storage::sqlite3_ondisk::write_varint_to_vec(serial_type_u64, blob);
value.serialize_serial(blob);
}
/// Deserialize a Value using SQLite's serial type format
/// Returns the deserialized value and the number of bytes consumed
pub fn deserialize_value(blob: &[u8]) -> Option<(Value, usize)> {
let mut cursor = 0;
// Read the serial type
let (serial_type, varint_size) = crate::storage::sqlite3_ondisk::read_varint(blob).ok()?;
cursor += varint_size;
let serial_type_obj = crate::types::SerialType::try_from(serial_type).ok()?;
let expected_size = serial_type_obj.size();
// Read the value
let (value, actual_size) =
crate::storage::sqlite3_ondisk::read_value(&blob[cursor..], serial_type_obj).ok()?;
// Verify that the actual size matches what we expected from the serial type
if actual_size != expected_size {
return None; // Data corruption - size mismatch
}
cursor += actual_size;
// Convert RefValue to Value
Some((value.to_owned(), cursor))
}
// group_key_str -> (group_key, state)
type ComputedStates = HashMap<String, (Vec<Value>, AggregateState)>;
// group_key_str -> (column_index, value_as_hashable_row) -> accumulated_weight
@@ -198,9 +267,9 @@ pub struct AggregateState {
// For COUNT: just the count
pub count: i64,
// For SUM: column_index -> sum value
sums: HashMap<usize, f64>,
pub sums: HashMap<usize, f64>,
// For AVG: column_index -> (sum, count) for computing average
avgs: HashMap<usize, (f64, i64)>,
pub avgs: HashMap<usize, (f64, i64)>,
// For MIN: column_index -> minimum value
pub mins: HashMap<usize, Value>,
// For MAX: column_index -> maximum value
@@ -306,11 +375,9 @@ impl AggregateEvalState {
// Only try to read if we have a rowid
if let Some(rowid) = rowid {
let key = SeekKey::TableRowId(*rowid);
let state = return_if_io!(read_record_state.read_record(
key,
&operator.aggregates,
&mut cursors.table_cursor
));
let state = return_if_io!(
read_record_state.read_record(key, &mut cursors.table_cursor)
);
// Process the fetched state
if let Some(state) = state {
let mut old_row = group_key.clone();
@@ -368,196 +435,249 @@ impl AggregateState {
Self::default()
}
// Serialize the aggregate state to a binary blob including group key values
// The reason we serialize it like this, instead of just writing the actual values, is that
// The same table may have different aggregators in the circuit. They will all have different
// columns.
fn to_blob(&self, aggregates: &[AggregateFunction], group_key: &[Value]) -> Vec<u8> {
let mut blob = Vec::new();
/// Convert the aggregate state to a vector of Values for unified serialization
/// Format: [count, num_aggregates, (agg_metadata, agg_state)...]
/// Each aggregate includes its type and column index for proper deserialization
pub fn to_value_vector(&self, aggregates: &[AggregateFunction]) -> Vec<Value> {
let mut values = Vec::new();
// Write version byte for future compatibility
blob.push(1u8);
// Include count first
values.push(Value::Integer(self.count));
// Write number of group key values
blob.extend_from_slice(&(group_key.len() as u32).to_le_bytes());
// Store number of aggregates
values.push(Value::Integer(aggregates.len() as i64));
// Write each group key value
for value in group_key {
// Write value type tag
match value {
Value::Null => blob.push(0u8),
Value::Integer(i) => {
blob.push(1u8);
blob.extend_from_slice(&i.to_le_bytes());
}
Value::Float(f) => {
blob.push(2u8);
blob.extend_from_slice(&f.to_le_bytes());
}
Value::Text(s) => {
blob.push(3u8);
let text_str = s.as_str();
let bytes = text_str.as_bytes();
blob.extend_from_slice(&(bytes.len() as u32).to_le_bytes());
blob.extend_from_slice(bytes);
}
Value::Blob(b) => {
blob.push(4u8);
blob.extend_from_slice(&(b.len() as u32).to_le_bytes());
blob.extend_from_slice(b);
}
}
}
// Write count as 8 bytes (little-endian)
blob.extend_from_slice(&self.count.to_le_bytes());
// Write each aggregate's state
// Add each aggregate's metadata and state
for agg in aggregates {
// First, add the aggregate function metadata (type and column index)
values.extend(agg.to_values());
// Then add the state for this aggregate
match agg {
AggregateFunction::Sum(col_name) => {
let sum = self.sums.get(col_name).copied().unwrap_or(0.0);
blob.extend_from_slice(&sum.to_le_bytes());
}
AggregateFunction::Avg(col_name) => {
let (sum, count) = self.avgs.get(col_name).copied().unwrap_or((0.0, 0));
blob.extend_from_slice(&sum.to_le_bytes());
blob.extend_from_slice(&count.to_le_bytes());
}
AggregateFunction::Count => {
// Count is already written above
// Count state is already stored at the beginning
}
AggregateFunction::Min(col_name) => {
// Write whether we have a MIN value (1 byte)
if let Some(min_val) = self.mins.get(col_name) {
blob.push(1u8); // Has value
serialize_value(min_val, &mut blob);
AggregateFunction::Sum(col_idx) => {
let sum = self.sums.get(col_idx).copied().unwrap_or(0.0);
values.push(Value::Float(sum));
}
AggregateFunction::Avg(col_idx) => {
let (sum, count) = self.avgs.get(col_idx).copied().unwrap_or((0.0, 0));
values.push(Value::Float(sum));
values.push(Value::Integer(count));
}
AggregateFunction::Min(col_idx) => {
if let Some(min_val) = self.mins.get(col_idx) {
values.push(Value::Integer(1)); // Has value
values.push(min_val.clone());
} else {
blob.push(0u8); // No value
values.push(Value::Integer(0)); // No value
}
}
AggregateFunction::Max(col_name) => {
// Write whether we have a MAX value (1 byte)
if let Some(max_val) = self.maxs.get(col_name) {
blob.push(1u8); // Has value
serialize_value(max_val, &mut blob);
AggregateFunction::Max(col_idx) => {
if let Some(max_val) = self.maxs.get(col_idx) {
values.push(Value::Integer(1)); // Has value
values.push(max_val.clone());
} else {
blob.push(0u8); // No value
values.push(Value::Integer(0)); // No value
}
}
}
}
blob
values
}
/// Deserialize aggregate state from a binary blob
/// Returns the aggregate state and the group key values
pub fn from_blob(blob: &[u8], aggregates: &[AggregateFunction]) -> Option<(Self, Vec<Value>)> {
/// Reconstruct aggregate state from a vector of Values
pub fn from_value_vector(values: &[Value]) -> Result<Self> {
let mut cursor = 0;
// Check version byte
if blob.get(cursor) != Some(&1u8) {
return None;
}
cursor += 1;
// Read number of group key values
let num_group_keys =
u32::from_le_bytes(blob.get(cursor..cursor + 4)?.try_into().ok()?) as usize;
cursor += 4;
// Read group key values
let mut group_key = Vec::new();
for _ in 0..num_group_keys {
let value_type = *blob.get(cursor)?;
cursor += 1;
let value = match value_type {
0 => Value::Null,
1 => {
let i = i64::from_le_bytes(blob.get(cursor..cursor + 8)?.try_into().ok()?);
cursor += 8;
Value::Integer(i)
}
2 => {
let f = f64::from_le_bytes(blob.get(cursor..cursor + 8)?.try_into().ok()?);
cursor += 8;
Value::Float(f)
}
3 => {
let len =
u32::from_le_bytes(blob.get(cursor..cursor + 4)?.try_into().ok()?) as usize;
cursor += 4;
let bytes = blob.get(cursor..cursor + len)?;
cursor += len;
let text_str = std::str::from_utf8(bytes).ok()?;
Value::Text(text_str.to_string().into())
}
4 => {
let len =
u32::from_le_bytes(blob.get(cursor..cursor + 4)?.try_into().ok()?) as usize;
cursor += 4;
let bytes = blob.get(cursor..cursor + len)?;
cursor += len;
Value::Blob(bytes.to_vec())
}
_ => return None,
};
group_key.push(value);
}
let mut state = Self::new();
// Read count
let count = i64::from_le_bytes(blob.get(cursor..cursor + 8)?.try_into().ok()?);
cursor += 8;
let count = values
.get(cursor)
.ok_or_else(|| LimboError::InternalError("Aggregate state missing count".into()))?;
if let Value::Integer(count) = count {
state.count = *count;
cursor += 1;
} else {
return Err(LimboError::InternalError(format!(
"Expected Integer for count, got {count:?}"
)));
}
let mut state = Self::new();
state.count = count;
// Read number of aggregates
let num_aggregates = values
.get(cursor)
.ok_or_else(|| LimboError::InternalError("Missing number of aggregates".into()))?;
let num_aggregates = match num_aggregates {
Value::Integer(n) => *n as usize,
_ => {
return Err(LimboError::InternalError(format!(
"Expected Integer for aggregate count, got {num_aggregates:?}"
)))
}
};
cursor += 1;
// Read each aggregate's state
for agg in aggregates {
match agg {
AggregateFunction::Sum(col_name) => {
let sum = f64::from_le_bytes(blob.get(cursor..cursor + 8)?.try_into().ok()?);
cursor += 8;
state.sums.insert(*col_name, sum);
}
AggregateFunction::Avg(col_name) => {
let sum = f64::from_le_bytes(blob.get(cursor..cursor + 8)?.try_into().ok()?);
cursor += 8;
let count = i64::from_le_bytes(blob.get(cursor..cursor + 8)?.try_into().ok()?);
cursor += 8;
state.avgs.insert(*col_name, (sum, count));
}
// Read each aggregate's state with type and column index
for _ in 0..num_aggregates {
// Deserialize the aggregate function metadata
let agg_fn = AggregateFunction::from_values(values, &mut cursor)?;
// Read the state for this aggregate
match agg_fn {
AggregateFunction::Count => {
// Count was already read above
// Count state is already stored at the beginning
}
AggregateFunction::Min(col_name) => {
// Read whether we have a MIN value
let has_value = *blob.get(cursor)?;
cursor += 1;
if has_value == 1 {
let (min_value, bytes_consumed) = deserialize_value(&blob[cursor..])?;
cursor += bytes_consumed;
state.mins.insert(*col_name, min_value);
AggregateFunction::Sum(col_idx) => {
let sum = values
.get(cursor)
.ok_or_else(|| LimboError::InternalError("Missing SUM value".into()))?;
if let Value::Float(sum) = sum {
state.sums.insert(col_idx, *sum);
cursor += 1;
} else {
return Err(LimboError::InternalError(format!(
"Expected Float for SUM value, got {sum:?}"
)));
}
}
AggregateFunction::Max(col_name) => {
// Read whether we have a MAX value
let has_value = *blob.get(cursor)?;
AggregateFunction::Avg(col_idx) => {
let sum = values
.get(cursor)
.ok_or_else(|| LimboError::InternalError("Missing AVG sum value".into()))?;
let sum = match sum {
Value::Float(f) => *f,
_ => {
return Err(LimboError::InternalError(format!(
"Expected Float for AVG sum, got {sum:?}"
)))
}
};
cursor += 1;
if has_value == 1 {
let (max_value, bytes_consumed) = deserialize_value(&blob[cursor..])?;
cursor += bytes_consumed;
state.maxs.insert(*col_name, max_value);
let count = values.get(cursor).ok_or_else(|| {
LimboError::InternalError("Missing AVG count value".into())
})?;
let count = match count {
Value::Integer(i) => *i,
_ => {
return Err(LimboError::InternalError(format!(
"Expected Integer for AVG count, got {count:?}"
)))
}
};
cursor += 1;
state.avgs.insert(col_idx, (sum, count));
}
AggregateFunction::Min(col_idx) => {
let has_value = values.get(cursor).ok_or_else(|| {
LimboError::InternalError("Missing MIN has_value flag".into())
})?;
if let Value::Integer(has_value) = has_value {
cursor += 1;
if *has_value == 1 {
let min_val = values
.get(cursor)
.ok_or_else(|| {
LimboError::InternalError("Missing MIN value".into())
})?
.clone();
cursor += 1;
state.mins.insert(col_idx, min_val);
}
} else {
return Err(LimboError::InternalError(format!(
"Expected Integer for MIN has_value flag, got {has_value:?}"
)));
}
}
AggregateFunction::Max(col_idx) => {
let has_value = values.get(cursor).ok_or_else(|| {
LimboError::InternalError("Missing MAX has_value flag".into())
})?;
if let Value::Integer(has_value) = has_value {
cursor += 1;
if *has_value == 1 {
let max_val = values
.get(cursor)
.ok_or_else(|| {
LimboError::InternalError("Missing MAX value".into())
})?
.clone();
cursor += 1;
state.maxs.insert(col_idx, max_val);
}
} else {
return Err(LimboError::InternalError(format!(
"Expected Integer for MAX has_value flag, got {has_value:?}"
)));
}
}
}
}
Some((state, group_key))
Ok(state)
}
fn to_blob(&self, aggregates: &[AggregateFunction], group_key: &[Value]) -> Vec<u8> {
let mut all_values = Vec::new();
// Store the group key size first
all_values.push(Value::Integer(group_key.len() as i64));
all_values.extend_from_slice(group_key);
all_values.extend(self.to_value_vector(aggregates));
let record = ImmutableRecord::from_values(&all_values, all_values.len());
record.as_blob().clone()
}
pub fn from_blob(blob: &[u8]) -> Result<(Self, Vec<Value>)> {
let record = ImmutableRecord::from_bin_record(blob.to_vec());
let ref_values = record.get_values();
let mut all_values: Vec<Value> = ref_values.into_iter().map(|rv| rv.to_owned()).collect();
if all_values.is_empty() {
return Err(LimboError::InternalError(
"Aggregate state blob is empty".into(),
));
}
// Read the group key size
let group_key_count = match &all_values[0] {
Value::Integer(n) if *n >= 0 => *n as usize,
Value::Integer(n) => {
return Err(LimboError::InternalError(format!(
"Negative group key count: {n}"
)))
}
other => {
return Err(LimboError::InternalError(format!(
"Expected Integer for group key count, got {other:?}"
)))
}
};
// Remove the group key count from the values
all_values.remove(0);
if all_values.len() < group_key_count {
return Err(LimboError::InternalError(format!(
"Blob too short: expected at least {} values for group key, got {}",
group_key_count,
all_values.len()
)));
}
// Split into group key and state values
let group_key = all_values[..group_key_count].to_vec();
let state_values = &all_values[group_key_count..];
// Reconstruct the aggregate state
let state = Self::from_value_vector(state_values)?;
Ok((state, group_key))
}
/// Apply a delta to this aggregate state