Added JSON Type

- Removed useless copy when ingesting JSON.
- Bugfix in phrase query with a missing field norms.
- Disabled range query on default fields

Closes #1251

CHANGELOG.md

@@ -9,6 +9,7 @@ Tantivy 0.17
 - Reduce the number of fsync calls [#1225](https://github.com/quickwit-oss/tantivy/issues/1225)
 - Fix opening bytes index with dynamic codec (@PSeitz) [#1278](https://github.com/quickwit-oss/tantivy/issues/1278)
 - Added an aggregation collector compatible with Elasticsearch (@PSeitz)
+- Added a JSON schema type @fulmicoton [#1251](https://github.com/quickwit-oss/tantivy/issues/1251)
 
 Tantivy 0.16.2
 ================================

benches/index-bench.rs

@@ -4,7 +4,7 @@ use tantivy::schema::{INDEXED, STORED, STRING, TEXT};
 use tantivy::Index;
 
 const HDFS_LOGS: &str = include_str!("hdfs.json");
-const NUM_REPEATS: usize = 10;
+const NUM_REPEATS: usize = 2;
 
 pub fn hdfs_index_benchmark(c: &mut Criterion) {
     let schema = {
@@ -21,6 +21,11 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
         schema_builder.add_text_field("severity", STRING | STORED);
         schema_builder.build()
     };
+    let dynamic_schema = {
+        let mut schema_builder = tantivy::schema::SchemaBuilder::new();
+        schema_builder.add_json_field("json", TEXT);
+        schema_builder.build()
+    };
 
     let mut group = c.benchmark_group("index-hdfs");
     group.sample_size(20);
@@ -74,6 +79,38 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
             index_writer.commit().unwrap();
         })
     });
+    group.bench_function("index-hdfs-no-commit-json-without-docstore", |b| {
+        b.iter(|| {
+            let index = Index::create_in_ram(dynamic_schema.clone());
+            let json_field = dynamic_schema.get_field("json").unwrap();
+            let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
+            for _ in 0..NUM_REPEATS {
+                for doc_json in HDFS_LOGS.trim().split("\n") {
+                    let json_val: serde_json::Map<String, serde_json::Value> =
+                        serde_json::from_str(doc_json).unwrap();
+                    let doc = tantivy::doc!(json_field=>json_val);
+                    index_writer.add_document(doc).unwrap();
+                }
+            }
+            index_writer.commit().unwrap();
+        })
+    });
+    group.bench_function("index-hdfs-with-commit-json-without-docstore", |b| {
+        b.iter(|| {
+            let index = Index::create_in_ram(dynamic_schema.clone());
+            let json_field = dynamic_schema.get_field("json").unwrap();
+            let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
+            for _ in 0..NUM_REPEATS {
+                for doc_json in HDFS_LOGS.trim().split("\n") {
+                    let json_val: serde_json::Map<String, serde_json::Value> =
+                        serde_json::from_str(doc_json).unwrap();
+                    let doc = tantivy::doc!(json_field=>json_val);
+                    index_writer.add_document(doc).unwrap();
+                }
+            }
+            index_writer.commit().unwrap();
+        })
+    });
 }
 
 criterion_group! {

bitpacker/benches/bench.rs

@@ -6,6 +6,7 @@ extern crate test;
 mod tests {
     use tantivy_bitpacker::BlockedBitpacker;
     use test::Bencher;
+
     #[bench]
     fn bench_blockedbitp_read(b: &mut Bencher) {
         let mut blocked_bitpacker = BlockedBitpacker::new();
@@ -20,6 +21,7 @@ mod tests {
             out
         });
     }
+
     #[bench]
     fn bench_blockedbitp_create(b: &mut Bencher) {
         b.iter(|| {

doc/src/json.md

@@ -0,0 +1,128 @@
+# Json
+
+As of tantivy 0.17, tantivy supports a json object type.
+This type can be used to allow for a schema-less search index.
+
+When indexing a json object, we "flatten" the JSON. This operation emits terms that represent a triplet `(json_path, value_type, value)`
+
+For instance,  if user is a json field, the following document:
+
+```json
+{
+    "user": {
+        "name": "Paul Masurel",
+        "address": {
+            "city": "Tokyo",
+            "country": "Japan"
+        },
+        "created_at": "2018-11-12T23:20:50.52Z"
+    }
+}
+```
+
+emits the following tokens:
+-  ("name", Text, "Paul")
+-  ("name", Text, "Masurel")
+-  ("address.city", Text, "Tokyo")
+-  ("address.country", Text, "Japan")
+-  ("created_at", Date, 15420648505)
+
+
+# Bytes-encoding and lexicographical sort.
+
+Like any other terms, these triplets are encoded into a binary format as follows.
+- `json_path`: the json path is a sequence of "segments". In the example above, `address.city`
+is just a debug representation of the json path `["address", "city"]`.
+Its representation is done by separating segments by a unicode char `\x01`, and ending the path by `\x00`.
+- `value type`: One byte represents the `Value` type.
+- `value`: The value representation is just the regular Value representation.
+
+This representation is designed to align the natural sort of Terms with the lexicographical sort
+of their binary representation (Tantivy's dictionary (whether fst or sstable) is sorted and does prefix encoding).
+
+In the example above, the terms will be sorted as
+-  ("address.city", Text, "Tokyo")
+-  ("address.country", Text, "Japan")
+-  ("name", Text, "Masurel")
+-  ("name", Text, "Paul")
+-  ("created_at", Date, 15420648505)
+
+As seen in "pitfalls", we may end up having to search for a value for a same path in several different fields. Putting the field code after the path makes it maximizes compression opportunities but also increases the chances for the two terms to end up in the actual same term dictionary block.
+
+
+# Pitfalls, limitation and corner cases.
+
+Json gives very little information about the type of the literals it stores.
+All numeric types end up mapped as a "Number" and there are no types for dates.
+
+At indexing, tantivy will try to interpret number and strings as different type with a
+priority order.
+
+Numbers will be interpreted as u64, i64 and f64 in that order.
+Strings will be interpreted as rfc3999 dates or simple strings.
+
+The first working type is picked and is the only term that is emitted for indexing.
+Note this interpretation happens on a per-document basis, and there is no effort to try to sniff
+a consistent field type at the scale of a segment.
+
+On the query parser side on the other hand, we may end up emitting more than one type.
+For instance, we do not even know if the type is a number or string based.
+
+So the query
+
+```
+my_path.my_segment:233
+```
+
+Will be interpreted as
+`(my_path.my_segment, String, 233) or (my_path.my_segment, u64, 233)`
+
+Likewise, we need to emit two tokens if the query contains an rfc3999 date.
+Indeed the date could have been actually a single token inside the text of a document at ingestion time. Generally speaking, we will always at least emit a string token in query parsing, and sometimes more.
+
+If one more json field is defined, things get even more complicated.
+
+
+## Default json field
+
+If the schema contains a text field called "text" and a json field that is set as a default field:
+`text:hello` could be reasonably interpreted as targetting the text field or as targetting the json field called `json_dynamic` with the json_path "text".
+
+If there is such an ambiguity, we decide to only search in the "text" field: `text:hello`.
+
+In other words, the parser will not search in default json fields if there is a schema hit.
+This is a product decision.
+
+The user can still target the JSON field by specifying its name explicitly:
+`json_dynamic.text:hello`.
+
+## Range queries are not supported.
+
+Json field do not support range queries.
+
+## Arrays do not work like nested object.
+
+If json object contains an array, a search query might return more documents
+than what might be expected.
+
+Let's take an example.
+
+```json
+{
+    "cart_id": 3234234 ,
+    "cart": [
+        {"product_type": "sneakers", "attributes": {"color": "white"} },
+        {"product_type": "t-shirt", "attributes": {"color": "red"}},
+    ]
+}
+```
+
+Despite the array structure, a document in tantivy is a bag of terms.
+The query:
+
+```
+cart.product_type:sneakers AND cart.attributes.color:red
+```
+
+Actually match the document above.
+

examples/json_field.rs

@@ -0,0 +1,80 @@
+// # Json field example
+//
+// This example shows how the json field can be used
+// to make tantivy partially schemaless.
+
+use tantivy::collector::{Count, TopDocs};
+use tantivy::query::QueryParser;
+use tantivy::schema::{Schema, FAST, STORED, STRING, TEXT};
+use tantivy::Index;
+
+fn main() -> tantivy::Result<()> {
+    // # Defining the schema
+    //
+    // We need two fields:
+    // - a timestamp
+    // - a json object field
+    let mut schema_builder = Schema::builder();
+    schema_builder.add_date_field("timestamp", FAST | STORED);
+    let event_type = schema_builder.add_text_field("event_type", STRING | STORED);
+    let attributes = schema_builder.add_json_field("attributes", STORED | TEXT);
+    let schema = schema_builder.build();
+
+    // # Indexing documents
+    let index = Index::create_in_ram(schema.clone());
+
+    let mut index_writer = index.writer(50_000_000)?;
+    let doc = schema.parse_document(
+        r#"{
+        "timestamp": "2022-02-22T23:20:50.53Z",
+        "event_type": "click",
+        "attributes": {
+            "target": "submit-button",
+            "cart": {"product_id": 103},
+            "description": "the best vacuum cleaner ever"
+        }
+    }"#,
+    )?;
+    index_writer.add_document(doc)?;
+    let doc = schema.parse_document(
+        r#"{
+        "timestamp": "2022-02-22T23:20:51.53Z",
+        "event_type": "click",
+        "attributes": {
+            "target": "submit-button",
+            "cart": {"product_id": 133},
+            "description": "das keyboard"
+        }
+    }"#,
+    )?;
+    index_writer.add_document(doc)?;
+    index_writer.commit()?;
+
+    let reader = index.reader()?;
+    let searcher = reader.searcher();
+
+    let query_parser = QueryParser::for_index(&index, vec![event_type, attributes]);
+    {
+        let query = query_parser.parse_query("target:submit-button")?;
+        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2))?;
+        assert_eq!(count_docs.len(), 2);
+    }
+    {
+        let query = query_parser.parse_query("target:submit")?;
+        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2))?;
+        assert_eq!(count_docs.len(), 2);
+    }
+    {
+        let query = query_parser.parse_query("cart.product_id:103")?;
+        let count_docs = searcher.search(&*query, &Count)?;
+        assert_eq!(count_docs, 1);
+    }
+    {
+        let query = query_parser
+            .parse_query("event_type:click AND cart.product_id:133")
+            .unwrap();
+        let hits = searcher.search(&*query, &TopDocs::with_limit(2)).unwrap();
+        assert_eq!(hits.len(), 1);
+    }
+    Ok(())
+}

query-grammar/src/user_input_ast.rs

@@ -59,15 +59,15 @@ pub enum UserInputBound {
 }
 
 impl UserInputBound {
-    fn display_lower(&self, formatter: &mut fmt::Formatter<'_>) -> Result<(), fmt::Error> {
+    fn display_lower(&self, formatter: &mut fmt::Formatter) -> Result<(), fmt::Error> {
         match *self {
             UserInputBound::Inclusive(ref word) => write!(formatter, "[\"{}\"", word),
             UserInputBound::Exclusive(ref word) => write!(formatter, "{{\"{}\"", word),
             UserInputBound::Unbounded => write!(formatter, "{{\"*\""),
         }
     }
 
-    fn display_upper(&self, formatter: &mut fmt::Formatter<'_>) -> Result<(), fmt::Error> {
+    fn display_upper(&self, formatter: &mut fmt::Formatter) -> Result<(), fmt::Error> {
         match *self {
             UserInputBound::Inclusive(ref word) => write!(formatter, "\"{}\"]", word),
             UserInputBound::Exclusive(ref word) => write!(formatter, "\"{}\"}}", word),

src/aggregation/mod.rs

@@ -243,7 +243,7 @@ pub(crate) fn f64_from_fastfield_u64(val: u64, field_type: &Type) -> f64 {
         Type::U64 => val as f64,
         Type::I64 => i64::from_u64(val) as f64,
         Type::F64 => f64::from_u64(val),
-        Type::Date | Type::Str | Type::Facet | Type::Bytes => unimplemented!(),
+        Type::Date | Type::Str | Type::Facet | Type::Bytes | Type::Json => unimplemented!(),
     }
 }
 
@@ -262,7 +262,7 @@ pub(crate) fn f64_to_fastfield_u64(val: f64, field_type: &Type) -> u64 {
         Type::U64 => val as u64,
         Type::I64 => (val as i64).to_u64(),
         Type::F64 => val.to_u64(),
-        Type::Date | Type::Str | Type::Facet | Type::Bytes => unimplemented!(),
+        Type::Date | Type::Str | Type::Facet | Type::Bytes | Type::Json => unimplemented!(),
     }
 }
 

src/core/segment_reader.rs

@@ -121,9 +121,8 @@ impl SegmentReader {
         self.fieldnorm_readers.get_field(field)?.ok_or_else(|| {
             let field_name = self.schema.get_field_name(field);
             let err_msg = format!(
-                "Field norm not found for field {:?}. Was the field set to record norm during \
-                 indexing?",
-                field_name
+                "Field norm not found for field {field_name:?}. Was the field set to record norm \
+                 during indexing?"
             );
             crate::TantivyError::SchemaError(err_msg)
         })

src/fastfield/multivalued/mod.rs

@@ -94,8 +94,11 @@ mod tests {
         assert_eq!(reader.num_docs(), 5);
 
         {
-            let parser = QueryParser::for_index(&index, vec![date_field]);
-            let query = parser.parse_query(&format!("\"{}\"", first_time_stamp.to_rfc3339()))?;
+            let parser = QueryParser::for_index(&index, vec![]);
+            let query = parser.parse_query(&format!(
+                "multi_date_field:\"{}\"",
+                first_time_stamp.to_rfc3339()
+            ))?;
             let results = searcher.search(&query, &TopDocs::with_limit(5))?;
             assert_eq!(results.len(), 1);
             for (_score, doc_address) in results {
@@ -150,7 +153,7 @@ mod tests {
         {
             let parser = QueryParser::for_index(&index, vec![date_field]);
             let range_q = format!(
-                "[{} TO {}}}",
+                "multi_date_field:[{} TO {}}}",
                 (first_time_stamp + Duration::seconds(1)).to_rfc3339(),
                 (first_time_stamp + Duration::seconds(3)).to_rfc3339()
             );