Microsoft Technology Licensing, LLC

Snowflake Inc.

Vikram Wakade

Benoit Dageville

Cristian Diaconu

Subramanian Muralidhar

Nithin Mahesh

Naveen Prakash

Yi Fang

Krystyna Ewa Reisteter

Lin Chan

Yiming Kang

Rishabh Singh Ahluwalia

Elkhan Mammedov

Lukas Moll

Martin Hentschel

Lyuping Du

Techniques for active invalidation of cache entries are described. A first timestamp and a second timestamp are stored by a compute instance, the first timestamp corresponding to an initial time the computing instance read from a version update log in a database and the second timestamp corresponding to a last time the computing instance read from the version update log in the database. The compute instance can read records from the version update log that are associated with version timestamps greater than the second timestamp. The compute instance can invalidate a first set of cache entries with older versions stored in a cache based on reading the records, retaining a second set of cache entries, and then execute a query using the second set of cache entries.

Active invalidation of metadata cache entries

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

Caching storage segments (e.g., pages) loaded from a remote storage such that, during recovery, the cached loaded storage segments may be at least partially recovered without reloading the storage segments from the remote storage. During normal operation of a computing system, storage segments are loaded from remote storage into local memory of a computing system. At some point, either due to eviction of the storage segment due to aging out of the storage segment, or due to writing of the storage segment, it is determined to write at least some of the loaded storage segments into local persistent storage. In conjunction with this, the corresponding storage segment is written to a respective storage address of the local persistent storage. Also, a correlation between an identifier of the storage segment and the respective address in the persistent storage is recorded in a persistent data structure.

Persistent storage segment caching for data recovery

A storage segment server environment that includes storage segment server(s) that cover a contiguous address space of data. The storage segment server has storage segments that are contiguous and that matches the address space of a respective of storage segments in the cloud store service. Thus, a read of the contiguous address spaces of the data from the cloud store service may instead be handled as a single read of the contiguous address space of the storage segment server. Each storage segment server(s) may be assigned to a range within the total contiguous address space of the data. Each storage segment server(s) includes a respective storage segment write component that is configured to perform write operations to storage segments in the respective storage segment server. Each storage segment server(s) also includes a respective cloud storage write component that initiates corresponding write operations to the cloud store service.

Storage segment server covered cache

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Sammamish, WA, United States of America

Vikram Wakade