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Derive schema by sampling database #6

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Mar 19, 2024
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10 changes: 9 additions & 1 deletion Cargo.lock

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1 change: 1 addition & 0 deletions crates/cli/Cargo.toml
Original file line number Diff line number Diff line change
Expand Up @@ -17,3 +17,4 @@ serde = { version = "1.0", features = ["derive"] }
serde_json = { version = "1.0.113", features = ["raw_value"] }
thiserror = "1.0.57"
tokio = { version = "1.36.0", features = ["full"] }
these = "2.0.0"
6 changes: 6 additions & 0 deletions crates/cli/src/introspection/mod.rs
Original file line number Diff line number Diff line change
@@ -0,0 +1,6 @@
pub mod sampling;
pub mod validation_schema;
pub mod type_unification;

pub use validation_schema::get_metadata_from_validation_schema;
pub use sampling::sample_schema_from_db;
163 changes: 163 additions & 0 deletions crates/cli/src/introspection/sampling.rs
Original file line number Diff line number Diff line change
@@ -0,0 +1,163 @@
use super::type_unification::{
unify_object_types, unify_schema, unify_type, TypeUnificationContext, TypeUnificationResult,
};
use configuration::{
schema::{Collection, ObjectField, ObjectType, Type},
Schema,
};
use futures_util::TryStreamExt;
use mongodb::bson::{doc, Bson, Document};
use mongodb_agent_common::interface_types::MongoConfig;
use mongodb_support::BsonScalarType::{self, *};

/// Sample from all collections in the database and return a Schema.
/// Return an error if there are any errors accessing the database
/// or if the types derived from the sample documents for a collection
/// are not unifiable.
pub async fn sample_schema_from_db(
sample_size: u32,
config: &MongoConfig,
) -> anyhow::Result<Schema> {
let mut schema = Schema {
collections: vec![],
object_types: vec![],
};
let db = config.client.database(&config.database);
let mut collections_cursor = db.list_collections(None, None).await?;

while let Some(collection_spec) = collections_cursor.try_next().await? {
let collection_name = collection_spec.name;
let collection_schema =
sample_schema_from_collection(&collection_name, sample_size, config).await?;
schema = unify_schema(schema, collection_schema)?;
}
Ok(schema)
}

async fn sample_schema_from_collection(
collection_name: &str,
sample_size: u32,
config: &MongoConfig,
) -> anyhow::Result<Schema> {
let db = config.client.database(&config.database);
let options = None;
let mut cursor = db
.collection::<Document>(collection_name)
.aggregate(vec![doc! {"$sample": { "size": sample_size }}], options)
.await?;
let mut collected_object_types = vec![];
while let Some(document) = cursor.try_next().await? {
let object_types = make_object_type(collection_name, &document)?;
collected_object_types = if collected_object_types.is_empty() {
object_types
} else {
unify_object_types(collected_object_types, object_types)?
};
}
let collection_info = Collection {
name: collection_name.to_string(),
description: None,
r#type: collection_name.to_string(),
};

Ok(Schema {
collections: vec![collection_info],
object_types: collected_object_types,
})
}

fn make_object_type(
object_type_name: &str,
document: &Document,
) -> TypeUnificationResult<Vec<ObjectType>> {
let (mut object_type_defs, object_fields) = {
let type_prefix = format!("{object_type_name}_");
let (object_type_defs, object_fields): (Vec<Vec<ObjectType>>, Vec<ObjectField>) = document
.iter()
.map(|(field_name, field_value)| {
make_object_field(&type_prefix, field_name, field_value)
})
.collect::<TypeUnificationResult<Vec<(Vec<ObjectType>, ObjectField)>>>()?
.into_iter()
.unzip();
(object_type_defs.concat(), object_fields)
};

let object_type = ObjectType {
name: object_type_name.to_string(),
description: None,
fields: object_fields,
};

object_type_defs.push(object_type);
Ok(object_type_defs)
}

fn make_object_field(
type_prefix: &str,
field_name: &str,
field_value: &Bson,
) -> TypeUnificationResult<(Vec<ObjectType>, ObjectField)> {
let object_type_name = format!("{type_prefix}{field_name}");
let (collected_otds, field_type) = make_field_type(&object_type_name, field_name, field_value)?;

let object_field = ObjectField {
name: field_name.to_owned(),
description: None,
r#type: field_type,
};

Ok((collected_otds, object_field))
}

fn make_field_type(
object_type_name: &str,
field_name: &str,
field_value: &Bson,
) -> TypeUnificationResult<(Vec<ObjectType>, Type)> {
fn scalar(t: BsonScalarType) -> TypeUnificationResult<(Vec<ObjectType>, Type)> {
Ok((vec![], Type::Scalar(t)))
}
match field_value {
Bson::Double(_) => scalar(Double),
Bson::String(_) => scalar(String),
Bson::Array(arr) => {
// Examine all elements of the array and take the union of the resulting types.
let mut collected_otds = vec![];
let mut result_type = Type::Scalar(Undefined);
for elem in arr {
let (elem_collected_otds, elem_type) =
make_field_type(object_type_name, field_name, elem)?;
collected_otds = if collected_otds.is_empty() {
elem_collected_otds
} else {
unify_object_types(collected_otds, elem_collected_otds)?
};
let context = TypeUnificationContext::new(object_type_name, field_name);
result_type = unify_type(context, result_type, elem_type)?;
}
Ok((collected_otds, Type::ArrayOf(Box::new(result_type))))
}
Bson::Document(document) => {
let collected_otds = make_object_type(object_type_name, document)?;
Ok((collected_otds, Type::Object(object_type_name.to_owned())))
}
Bson::Boolean(_) => scalar(Bool),
Bson::Null => scalar(Null),
Bson::RegularExpression(_) => scalar(Regex),
Bson::JavaScriptCode(_) => scalar(Javascript),
Bson::JavaScriptCodeWithScope(_) => scalar(JavascriptWithScope),
Bson::Int32(_) => scalar(Int),
Bson::Int64(_) => scalar(Long),
Bson::Timestamp(_) => scalar(Timestamp),
Bson::Binary(_) => scalar(BinData),
Bson::ObjectId(_) => scalar(ObjectId),
Bson::DateTime(_) => scalar(Date),
Bson::Symbol(_) => scalar(Symbol),
Bson::Decimal128(_) => scalar(Decimal),
Bson::Undefined => scalar(Undefined),
Bson::MaxKey => scalar(MaxKey),
Bson::MinKey => scalar(MinKey),
Bson::DbPointer(_) => scalar(DbPointer),
}
}
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