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https://issues.apache.org/jira/browse/PHOENIX-7330?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Viraj Jasani resolved PHOENIX-7330.
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Resolution: Fixed
> Introducing Binary JSON (BSON) with Complex Document structures in Phoenix
> --------------------------------------------------------------------------
>
> Key: PHOENIX-7330
> URL: https://issues.apache.org/jira/browse/PHOENIX-7330
> Project: Phoenix
> Issue Type: New Feature
> Reporter: Viraj Jasani
> Assignee: Viraj Jasani
> Priority: Major
> Fix For: 5.3.0
>
>
> The purpose of this Jira is to introduce new data type in Phoenix: Binary
> JSON (BSON) to manage more complex document data structures in Phoenix.
> BSON or Binary JSON is a Binary-Encoded serialization of JSON-like documents.
> BSON data type is specifically used for users to store, update and query part
> or whole of the BsonDocument in the most performant way without having to
> serialize/deserialize the document to/from binary format. Bson allows
> deserializing only part of the nested documents such that querying or
> indexing any attributes within the nested structure becomes more efficient
> and performant as the deserialization happens at runtime. Any other document
> structure would require deserializing the binary into the document, and then
> perform the query.
> BSONSpec: [https://bsonspec.org/]
> JSON and BSON are closely related by design. BSON serves as a binary
> representation of JSON data, tailored with specialized extensions for wider
> application scenarios, and finely tuned for efficient data storage and
> traversal. Similar to JSON, BSON facilitates the embedding of objects and
> arrays.
> One particular way in which BSON differs from JSON is in its support for some
> more advanced data types. For instance, JSON does not differentiate between
> integers (round numbers), and floating-point numbers (with decimal
> precision). BSON does distinguish between the two and store them in the
> corresponding BSON data type (e.g. BsonInt32 vs BsonDouble). Many server-side
> programming languages offer advanced numeric data types (standards include
> integer, regular precision floating point number i.e. “float”,
> double-precision floating point i.e. “double”, and boolean values), each with
> its own optimal usage for efficient mathematical operations.
> Another key distinction between BSON and JSON is that BSON documents have the
> capability to include Date or Binary objects, which cannot be directly
> represented in pure JSON format. BSON also provides the ability to store and
> retrieve user defined Binary objects. Likewise, by integrating advanced data
> structures like Sets into BSON documents, we can significantly enhance the
> capabilities of Phoenix for storing, retrieving, and updating Binary, Sets,
> Lists, and Documents as nested or complex data types.
> Moreover, JSON format is human as well as machine readable, whereas BSON
> format is only machine readable. Hence, as part of introducing BSON data
> type, we also need to provide a user interface such that users can provide
> human readable JSON as input for BSON datatype.
> This Jira also introduces access and update functions for BSON documents.
> BSON_CONDITION_EXPRESSION can evaluate condition expression on the document
> fields, similar to how WHERE clause evaluates condition expression on various
> columns of the given row(s) for the relational tables.
> BSON_UPDATE_EXPRESSION can perform one or more document field updates similar
> to how UPSERT statements can perform update to one or more columns of the
> given row(s) for the relational tables.
>
> Phoenix can introduce more complex data structures like sets of scalar types,
> in addition to the nested documents and nested arrays provided by BSON.
> Overall, by combining various functionalities available in Phoenix like
> secondary indexes, conditional updates, high throughput read/write with BSON,
> we can evolve Phoenix into highly scalable Document Database.
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