MongoDB, Inc.

A system is provided for storing, in a database, a plurality of timeseries represented by a plurality of respective documents events in a columnar format. The system further is adapted compress at least one of the values within the plurality of documents. According to some embodiments, the system stores the compressed values as a Simple-8b block and calculates the optimal Simple-8b selector. According to some embodiments, the system is adapted to determine a secondary index based on values within the bucket.

According to some aspects, provided are systems and methods that implement end-to-end encryption, and provide implementation configured to secure information during execution of queries on an encrypted data source. Various embodiments include multiple encrypted multi-map data structures and associated encryption schemes configured to securely read, write, and delete information while supporting any one or more of the following features: snapshot security, multiple client support, efficient execution under concurrent operation, and resilience to client failures. In various embodiments, addressable multi-map data structures enable concurrent access, and allow correct operation under polynomial time constraints.

A system is provided for storing, in a database, a plurality of timeseries represented by a plurality of respective documents events in a columnar format. The system further is adapted compress at least one of the values within the plurality of documents. According to some embodiments, the system stores the compressed values as a Simple-8b block and calculates the optimal Simple-8b selector. According to some embodiments, the system is adapted to determine a secondary index based on values within the bucket.

Described herein embodiments of a query processing system. The query processing system optimizes execution by generating an optimized slot-based execution (SBE) plan for executing the query. The query processing system optimizes query execution by generating a logical representation of the query, optimizing the logical representation of the query, and translating the optimized logical representation of the query into an SBE plan. The query processing system then executes the SBE plan to generate the query results.

A system comprising a pipeline is provided comprising a first stage configured to create a plurality of BSON documents from input data, a block processing stage configured to format the plurality of BSON documents into one or more blocks and to provide an access interface to the one or more blocks, a query stage configured to execute a query to the one or more blocks using the access interface to generate an output array responsive to the query; and a decomposition stage configured to transform the output array into one or more slots of scalar data values.

Provided is a system for processing semi-structured data, comprising a tokenization module configured to convert JSON objects into token sequences by recursively traversing keys and values (e.g., in depth-first order) and generating sequences of key tokens, value tokens, and grammatical tokens, wherein key tokens are distinguished from value tokens through a transformation that wraps original key strings in a special token format. The system includes a positional encoding module configured to generate hierarchical position embeddings using a PDA that maintains a stack reflecting parsing state, wherein the positional encoding module computes position embeddings by summing embeddings of stack symbols present at each sequence position. A transformer architecture comprising multiple layers of self-attention mechanisms is configured to process combined token and position embeddings. A grammar validation module is configured to enforce valid token sequences by suppressing logits corresponding to invalid transitions according to JSON grammar rules encoded in the PDA.

According to some aspects, provided are systems and methods that implement end-to-end encryption, and provide implementation configured to secure information during execution of queries on an encrypted data source. Various embodiments include multiple encrypted multi-map data structures and associated encryption schemes configured to securely read, write, and delete information while supporting any one or more of the following features: snapshot security, multiple client support, efficient execution under concurrent operation, and resilience to client failures. In various embodiments, addressable multi-map data structures enable concurrent access, and allow correct operation under polynomial time constraints.

Systems and methods are configured to identify and resolve user-based issues, architecture issues, and data model issues that are introduced into distributed database deployments. Even in the context of a pre-built distributed database system, “bad” user behavior can have huge impacts on database performance. Various embodiments provide for analysis and resolution of architecture issues, as well schema issues, and can be configured to identify and resolve such problems in the context of dynamic schema database systems. Unlike relational database counterparts, dynamic schema databases do not enforce static database architecture or defined schemas. In such environments, database data and database formatting can be mostly unconstrained. If used properly, this flexibility enables easy configuration and execution. However, when improperly designed, small flaws magnify in significance as the database grows. Various embodiments identify anti-patterns indicative of non-optimal configuration or bad performance, and generate options for resolving them.

A system and computer implemented method for execution of aggregation expressions on a distributed non-relational database system is provided. According to one aspect, an aggregation operation may be provided that permits more complex operations using separate collections. For instance, it may be desirable to create a report from one collection using information grouped according to information stored in another collection. Such a capability may be provided within other conventional database systems, however, in a non-relational database system such as NoSQL, the system is not capable of performing server-side joins, such a capability may not be performed without denormalizing the attributes into each object that references it, or by performing application-level joins which is not efficient and leads to unnecessarily complex code within the application that interfaces with the NoSQL database system.

Described herein embodiments of a query processing system. The query processing system optimizes execution by generating an optimized slot-based execution (SBE) plan for executing the query. The query processing system optimizes query execution by generating a logical representation of the query, optimizing the logical representation of the query, and translating the optimized logical representation of the query into an SBE plan. The query processing system then executes the SBE plan to generate the query results.