Snowflake Inc.

Lin Chan

Nithin Mahesh

Eric Robinson

Tianyi Chen

Yiming Kang

Benoit Dageville

Robert Bengt Benedikt Gernhardt

Jun Luo

Brian Smith

Subramanian Muralidhar

Sahaj Saini

Yi Fang

Sarvesh Singh

Vikram Wakade

Krishna B Nibhanupudi

Rishabh Singh Ahluwalia

As described herein, a N-Gram index may be created and the search may be conducted using the index, which will lead to faster search results. The N-Gram index may also include partial N-Gram components to capture more relevant data. Moreover, as described herein, the search may also take into account recent log data that has not yet been indexed. Techniques for building an index store using log data and efficiently searching the index store and log data to process search requests are described herein.

Metadata search via N-gram index

Techniques for constructing transaction lock wait history showing blocker queries are described. A first transaction referencing a resource saved in a network-based data warehouse is received where the first transaction being blocked due to second transaction accessing the resource. A first telemetry event based on the first transaction being blocked is transmitted. After acquiring lock ownership of the resource by the first transaction, a second telemetry event based on acquiring lock ownership by the first transaction is transmitted.

Event driven technique for constructing transaction lock wait history

Techniques for executing show commands are described herein. A plurality of navigation steps is utilized, each navigation step corresponding to a different layer in a database structure and each navigation step including an operator to fetch items from a metadata database up to respective bounded limits. Dependency information is also fetched for objects of the specified object type in the show command. After a set of objects from the last layer are processed, memory for the navigation steps is flushed and the next set of objects are processed.

Catalog query framework on distributed key value store

Described herein are techniques for compact representation of table columns via templatization. Column templates can model the collection of columns in a table as a logical entity. The logical entity can be split into two objects. A first object can contain a subset of column attributes (e.g., fields) that can be shared with other tables, such as name and data type. A second object can contain another subset of column attributes that are unique to a table, such as time stamps and created-on information.

Compact representation of table columns via templatization

Metadata search via N-Gram index

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Bellevue, WA, United States of America

Lin Chan