Snowflake Inc.

Raghav Ramachandran

Ganeshan Ramachandran Iyer

Subramanian Muralidhar

Nithin Mahesh

Jiaxing Liang

Abdullah Al Mahmood

Xin Huang

Purav B Saraiya

Ruta Dhaneshwar

Yanyi Zhang

Yang Wang

Techniques for deduplicating files to be ingested by a database are disclosed. A bloom filter may be built for each of a first set of files to be ingested into a data exchange to generate a set of bloom filters, wherein each of the set of bloom filters is built with a number of hash functions that is based on a desired false positive rate. The set of bloom filters may be stored in the metadata storage of the data exchange. In response to receiving a set of candidate files to be ingested, identifying using the set of bloom filters, candidate files from the set of candidate files that are duplicative of a file in the first set of files and pruning from the set of candidate files, each candidate file identified as being duplicative of a file in the first set of files using the set of bloom filters.

Efficient deduplication of randomized file paths

A system and method of dynamic task allocation and warehouse scaling. The method includes receiving a request to process a task. The method includes monitoring a plurality of execution nodes of a datastore to determine a plurality of central processing unit (CPU) utilizations. Each CPU utilization of the plurality of CPU utilizations is associated with a respective execution node of the plurality of execution nodes. The method includes identifying, by a processing device based on the plurality of CPU utilizations, a particular execution node associated with a maximum CPU utilization to process the task. The method includes allocating the task to the particular execution node.

Dynamic task allocation and datastore scaling

A data transfer request can be received by each of multiple deployments; however, only a primary deployment can process the request. The data transferred by the primary deployment may be replicated in the secondary deployments. In response to a failover event, one of the secondary deployments can be designated as the new primary development and continue the data transfer based on the data transfer request and the replication information received from the old primary deployment prior to the failover.

Data ingestion replication and disaster recovery

Disclosed are techniques for deduplicating files to be ingested by a database. A bloom filter may be built for each of a first set of files to be ingested into a data exchange to generate a set of bloom filters, wherein the data exchange includes a metadata storage where metadata including a list of files ingested is stored. The set of bloom filters may be stored in the metadata storage of the data exchange. In response to receiving a set of candidate files to be ingested into the data exchange, the set of bloom filters may be used to identify from within the set of candidate files, each candidate file that is duplicative of a file in the first set of files.

Described herein are techniques for improving disaster recovery, in particular disaster recovery pertaining to data transfer requests. The data transfer request can be received by each of multiple deployments; however, only a primary deployment can process the request. The data transferred by the primary deployment may be replicated in the secondary deployments. In response to a failover event, one of the secondary deployments can be designated as the new primary development and continue the data transfer based on the data transfer request and the replication information received from the old primary deployment prior to the failover.

Embodiments of the present disclosure provide techniques for deduplicating files to be ingested by a database. A bloom filter may be built for each of a first set of files that are ingested into the database. The set of bloom filters may be stored in a metadata storage associated with the database along with file loading metadata of the first set of files. In response to receiving a set of candidate files to be ingested into the database, one or more candidate files that are duplicative of a file in the first set of files are removed from the set of candidate files, based on file loading metadata of each the first set of files and the set of candidate files to generate a reduced set of candidate files. From the reduced set of candidate files, candidate files that are not duplicative are identified and set for ingestion while candidate files that are potentially duplicative are also identified and set for further scanning.

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Seattle, WA, United States of America

Raghav Ramachandran