Snowflake Inc.

Mahmud Allahverdiyev

Ismail Oukid

Thierry Cruanes

Stefan Richter

Selcuk Aya

Matthias Carl Adams

Bowei Chen

Alejandro Salinger

Peter Popov

A method to perform an indexed geospatial search includes retrieving, by at least one hardware processor, a query specifying a geography data column and a constant geography object. A first plurality of hash functions of a first set of cells covering a surface associated with the geography data column is determined. A search index of a database including the geography data column is updated based on the first plurality of hash functions to obtain an updated search index. The query is executed on a reduced scan set of the database. The reduced scan set is based on the updated search index.

Indexed geospatial search

Provided herein are systems and methods for indexed geospatial predicate search. An example method performed by at least one hardware processor includes decoding a query with a geospatial predicate. The geospatial predicate is configured between a geography data column and a constant geography object. The method further includes computing a first covering for a data value of a plurality of data values in the geography data column. The first covering includes a first set of cells in a hierarchical grid representation of a geography. The first set of cells represents a surface of the geography associated with the data value. A second covering is computed for the constant geography object. A determination is made on whether to prune at least one partition of a database organized into a set of partitions and including the geography data column based on a comparison between the first covering and the second covering.

Indexed geospatial predicate search

A source table organized into a set of batch units is accessed. The source table comprises a column of data corresponding to a semi-structured data type. One or more indexing transformations for an object in the column are generated. The generating of the one or more indexing transformation includes converting the object to one or more stored data types. A pruning index is generated for the source table based in part on the one or more indexing transformations. The pruning index comprises a set of filters that index distinct values in each column of the source table, and each filter corresponds to a batch unit in the set of batch units. The pruning index is stored in a database with an association with the source table.

Scan set pruning for queries with predicates on semi-structured fields

A pruning index is generated for a source table organized into a set of batch units. The source table comprises a column of semi-structured data. The pruning index comprises a set of filters that index distinct values in each column of the source table. Rather than reassembling an entire tree structure of the semi-structured data prior to indexing, the generating of the pruning index comprises traversing a reassembly hook object that represents a first portion of the semi-structured data that is subcolumnarized and traversing a residual object that represents a second portion of the semi-structured data that is not subcolumnarized. The reassembly hook object is traversed to identify values corresponding to the first portion of the semi-structured data and the residual object is traversed to identify values corresponding to the second portion. The pruning index is stored with an association with the source table.

Index generation using lazy reassembling of semi-structured data

Lazy reassembling of semi-structured data

Processing queries on semi-structured data columns

Pruning index to support semi-structured data types

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Berlin, Germany

Mahmud Allahverdiyev