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use serde_json::Value;
/// 过滤条件表达式
/// 支持: $eq, $ne, $gt, $gte, $lt, $lte, $in, $and, $or
#[derive(Debug, Clone)]
pub enum Filter {
/// 精确匹配: {"field": {"$eq": value}}
Eq(String, Value),
/// 不等于
Ne(String, Value),
/// 大于 (仅数字)
Gt(String, f64),
/// 大于等于
Gte(String, f64),
/// 小于
Lt(String, f64),
/// 小于等于
Lte(String, f64),
/// 值在集合中: {"field": {"$in": [v1, v2]}}
In(String, Vec<Value>),
/// 逻辑与
And(Vec<Filter>),
/// 逻辑或
Or(Vec<Filter>),
/// 字段是否存在
Exists(String, bool),
/// 值不在集合中
Nin(String, Vec<Value>),
/// 数组长度匹配
Size(String, usize),
/// 数组包含所有指定元素
All(String, Vec<Value>),
/// 字段类型匹配
TypeMatch(String, String),
}
impl Filter {
/// 检查一个 JSON payload 是否满足该过滤条件
pub fn matches(&self, payload: &Value) -> bool {
match self {
Filter::Eq(key, val) => payload.get(key) == Some(val),
Filter::Ne(key, val) => payload.get(key) != Some(val),
Filter::Gt(key, threshold) => {
extract_number(payload, key).is_some_and(|v| v > *threshold)
}
Filter::Gte(key, threshold) => {
extract_number(payload, key).is_some_and(|v| v >= *threshold)
}
Filter::Lt(key, threshold) => {
extract_number(payload, key).is_some_and(|v| v < *threshold)
}
Filter::Lte(key, threshold) => {
extract_number(payload, key).is_some_and(|v| v <= *threshold)
}
Filter::In(key, values) => {
if let Some(field_val) = payload.get(key) {
values.contains(field_val)
} else {
false
}
}
Filter::Exists(key, exists) => payload.get(key).is_some() == *exists,
Filter::Nin(key, values) => {
if let Some(field_val) = payload.get(key) {
!values.contains(field_val)
} else {
true
}
}
Filter::Size(key, size) => payload
.get(key)
.and_then(|v| v.as_array())
.is_some_and(|arr| arr.len() == *size),
Filter::All(key, values) => payload
.get(key)
.and_then(|v| v.as_array())
.is_some_and(|arr| values.iter().all(|val| arr.contains(val))),
Filter::TypeMatch(key, type_str) => {
if let Some(v) = payload.get(key) {
let actual_type = match v {
Value::Null => "null",
Value::Bool(_) => "boolean",
Value::Number(_) => "number",
Value::String(_) => "string",
Value::Array(_) => "array",
Value::Object(_) => "object",
};
actual_type == type_str.as_str()
} else {
false
}
}
Filter::And(filters) => filters.iter().all(|f| f.matches(payload)),
Filter::Or(filters) => filters.iter().any(|f| f.matches(payload)),
}
}
/// 提取出本查询必然要求的特征哈希位掩码（布隆过滤掩码）
/// 用于在查询图谱全量数组时，实现超音速 O(N) 一级降维打击
pub fn extract_must_have_mask(&self) -> u64 {
match self {
Filter::Eq(key, val) => {
let mut hasher = std::collections::hash_map::DefaultHasher::new();
use std::hash::{Hash, Hasher};
// Consistent with how fast_tags hashes values
let val_str = match val {
Value::String(s) => s.clone(),
v => v.to_string(),
};
format!("{}:{}", key, val_str).hash(&mut hasher);
1u64 << (hasher.finish() % 64)
}
Filter::And(filters) => {
let mut mask = 0u64;
for f in filters {
mask |= f.extract_must_have_mask();
}
mask
}
// 对于 Or, In, Gt 等操作，我们无法提取单根必达掩码，安全退化为0（即退化到原版全扫描）
_ => 0,
}
}
// ════════ Builder 便捷方法 ════════
pub fn eq(key: impl Into<String>, val: Value) -> Self {
Filter::Eq(key.into(), val)
}
pub fn ne(key: impl Into<String>, val: Value) -> Self {
Filter::Ne(key.into(), val)
}
pub fn gt(key: impl Into<String>, val: f64) -> Self {
Filter::Gt(key.into(), val)
}
pub fn gte(key: impl Into<String>, val: f64) -> Self {
Filter::Gte(key.into(), val)
}
pub fn lt(key: impl Into<String>, val: f64) -> Self {
Filter::Lt(key.into(), val)
}
pub fn lte(key: impl Into<String>, val: f64) -> Self {
Filter::Lte(key.into(), val)
}
pub fn is_in(key: impl Into<String>, vals: Vec<Value>) -> Self {
Filter::In(key.into(), vals)
}
pub fn and(filters: Vec<Filter>) -> Self {
Filter::And(filters)
}
pub fn or(filters: Vec<Filter>) -> Self {
Filter::Or(filters)
}
pub fn exists(key: impl Into<String>, e: bool) -> Self {
Filter::Exists(key.into(), e)
}
pub fn nin(key: impl Into<String>, vals: Vec<Value>) -> Self {
Filter::Nin(key.into(), vals)
}
pub fn size(key: impl Into<String>, s: usize) -> Self {
Filter::Size(key.into(), s)
}
pub fn all(key: impl Into<String>, vals: Vec<Value>) -> Self {
Filter::All(key.into(), vals)
}
pub fn type_match(key: impl Into<String>, t: impl Into<String>) -> Self {
Filter::TypeMatch(key.into(), t.into())
}
/// 从 JSON Value 解析为 Filter（类 MongoDB 语法）
///
/// 支持的语法示例：
/// - `{"age": {"$gt": 18}}` → `Filter::Gt("age", 18.0)`
/// - `{"$and": [{...}, {...}]}` → `Filter::And([...])`
/// - `{"name": "Alice"}` → `Filter::Eq("name", "Alice")`（隐式 $eq）
pub fn from_json(val: &Value) -> Result<Self, String> {
let obj = val
.as_object()
.ok_or_else(|| "过滤条件必须是 JSON 对象".to_string())?;
let mut filters = Vec::new();
for (key, v) in obj {
match key.as_str() {
"$and" => {
let arr = v.as_array().ok_or_else(|| "$and 必须是数组".to_string())?;
let sub: Result<Vec<Filter>, String> =
arr.iter().map(Filter::from_json).collect();
filters.push(Filter::And(sub?));
}
"$or" => {
let arr = v.as_array().ok_or_else(|| "$or 必须是数组".to_string())?;
let sub: Result<Vec<Filter>, String> =
arr.iter().map(Filter::from_json).collect();
filters.push(Filter::Or(sub?));
}
field => {
if let Some(op_obj) = v.as_object() {
// 运算符语法: {"field": {"$gt": 18}}
for (op, op_val) in op_obj {
let f = match op.as_str() {
"$eq" => Filter::Eq(field.to_string(), op_val.clone()),
"$ne" => Filter::Ne(field.to_string(), op_val.clone()),
"$gt" => Filter::Gt(
field.to_string(),
op_val.as_f64().ok_or_else(|| "$gt 需要数字".to_string())?,
),
"$gte" => Filter::Gte(
field.to_string(),
op_val.as_f64().ok_or_else(|| "$gte 需要数字".to_string())?,
),
"$lt" => Filter::Lt(
field.to_string(),
op_val.as_f64().ok_or_else(|| "$lt 需要数字".to_string())?,
),
"$lte" => Filter::Lte(
field.to_string(),
op_val.as_f64().ok_or_else(|| "$lte 需要数字".to_string())?,
),
"$in" => {
let arr = op_val
.as_array()
.ok_or_else(|| "$in 需要数组".to_string())?;
Filter::In(field.to_string(), arr.clone())
}
"$nin" => {
let arr = op_val
.as_array()
.ok_or_else(|| "$nin 需要数组".to_string())?;
Filter::Nin(field.to_string(), arr.clone())
}
"$exists" => {
let b = op_val
.as_bool()
.ok_or_else(|| "$exists 需要布尔值".to_string())?;
Filter::Exists(field.to_string(), b)
}
"$size" => {
let n = op_val
.as_u64()
.ok_or_else(|| "$size 需要正整数".to_string())?
as usize;
Filter::Size(field.to_string(), n)
}
"$all" => {
let arr = op_val
.as_array()
.ok_or_else(|| "$all 需要数组".to_string())?;
Filter::All(field.to_string(), arr.clone())
}
"$type" => {
let t = op_val
.as_str()
.ok_or_else(|| "$type 需要字符串".to_string())?;
Filter::TypeMatch(field.to_string(), t.to_string())
}
unknown => return Err(format!("未知操作符: {}", unknown)),
};
filters.push(f);
}
} else {
// 隐式 $eq 语法: {"name": "Alice"}
filters.push(Filter::Eq(field.to_string(), v.clone()));
}
}
}
}
match filters.len() {
0 => Err("过滤条件不能为空".to_string()),
1 => Ok(filters
.into_iter()
.next()
.expect("BUG: len==1 but next() returned None")),
_ => Ok(Filter::And(filters)),
}
}
}
fn extract_number(payload: &Value, key: &str) -> Option<f64> {
payload.get(key)?.as_f64()
}