Abstract: 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.

Abstract: A table organized into a set of batch units is accessed. A set of N-grams are generated for a data value in the source table. The set of N-grams include a first N-gram of a first length and a second N-gram of a second length where the first N-gram corresponds to a prefix of the second N-gram. A set of fingerprints are generated for the data value based on the set of N-grams. The set of fingerprints include a first fingerprint generated based on the first N-gram and a second fingerprint generated based on the second N-gram and the first fingerprint. A pruning index that indexes distinct values in each column of the source table is generated based on the set of fingerprints and stored in a database with an association with the source table.

Abstract: A query directed at a table organized into a set of batch units is received. The query comprises a predicate for which values are unknown prior to runtime. A set of values for the predicate are determined based on the query. An index access plan is created based on the set of values. Based on the index access plan, the set of batch units are pruned using a pruning index associated with the table. The pruning index comprises a set of filters that index distinct values in each column of the table. The pruning of the set of batch units comprises identifying a subset of batch units to scan for data that satisfies the query. The subset of batch units of the table are scanned to identify data that satisfies the query.

Abstract: 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.

Abstract: A source table organized into a set of micro-partitions is accessed by a network-based data warehouse. A pruning index is generated based on the source table. The pruning index comprises a set of filters that indicate locations of distinct values in each column of the source table. A query directed at the source table is received at the network-based data warehouse. The query is processed using the pruning index. The processing of the query comprises pruning the set of micro-partitions of the source table to scan for data matching the query, the pruning of the plurality of micro-partitions comprising identifying, using the pruning index, a sub-set of micro-partitions to scan for the data matching the query.

Abstract: Techniques and solutions are described for implementing virtual domains. Computing resources in a computing environment are determined and assigned to one or more virtual domains. One or more data structures can be located in a given virtual domain. The computing resources assigned to a virtual domain can be dynamically reconfigured without affecting processes that submit tasks to be performed on data structures in the virtual domains. Tasks can be submitted to a dispatcher, which can determine the appropriate virtual domain for the task and forward the task to the determined virtual domain. Tasks are received by virtual domains and assigned to worker threads, which can access a data structure specified for a given task.

Abstract: A query directed at a source table organized into a set of batch units is received. The query includes a pattern matching predicate that specifies a search pattern. A set of N-grams are generated based on the search pattern. A pruning index associated with the source table is accessed. The pruning index comprises a set of filters that index distinct N-grams in each column of the source table. The pruning index is used to identify a subset of batch units to scan for matching data based on the set of N-grams generated for the search pattern. The query is processed by scanning the subset of batch units.

Abstract: 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.

Abstract: A query directed at a table organized into a set of batch units is received. The query comprises a predicate for which values are unknown prior to runtime. A set of values for the predicate are determined based on the query. An index access plan is created based on the set of values. Based on the index access plan, the set of batch units are pruned using a pruning index associated with the table. The pruning index comprises a set of filters that index distinct values in each column of the table. The pruning of the set of batch units comprises identifying a subset of batch units to scan for data that satisfies the query. The subset of batch units of the table are scanned to identify data that satisfies the query.

Abstract: A table organized into a set of batch units is accessed. A set of N-grams are generated for a data value in the source table. The set of N-grams include a first N-gram of a first length and a second N-gram of a second length where the first N-gram corresponds to a prefix of the second N-gram. A set of fingerprints are generated for the data value based on the set of N-grams. The set of fingerprints include a first fingerprint generated based on the first N-gram and a second fingerprint generated based on the second N-gram and the first fingerprint. A pruning index that indexes distinct values in each column of the source table is generated based on the set of fingerprints and stored in a database with an association with the source table.

Abstract: A query directed at a source table organized into a set of batch units is received. The query includes a pattern matching predicate that specifies a search pattern. A set of N-grams are generated based on the search pattern. A pruning index associated with the source table is accessed. The pruning index comprises a set of filters that index distinct N-grams in each column of the source table. The pruning index is used to identify a subset of batch units to scan for matching data based on the set of N-grams generated for the search pattern. The query is processed by scanning the subset of batch units.

Abstract: 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.

Abstract: A source table organized into a set of micro-partitions is accessed by a network-based data warehouse. A pruning index is generated based on the source table. The pruning index comprises a set of filters that indicate locations of distinct values in each column of the source table. A query directed at the source table is received at the network-based data warehouse. The query is processed using the pruning index. The processing of the query comprises pruning the set of micro-partitions of the source table to scan for data matching the query, the pruning of the plurality of micro-partitions comprising identifying, using the pruning index, a sub-set of micro-partitions to scan for the data matching the query.

Abstract: Techniques and solutions are described for implementing virtual domains. Computing resources in a computing environment are determined and assigned to one or more virtual domains. One or more data structures can be located in a given virtual domain. The computing resources assigned to a virtual domain can be dynamically reconfigured without affecting processes that submit tasks to be performed on data structures in the virtual domains. Tasks can be submitted to a dispatcher, which can determine the appropriate virtual domain for the task and forward the task to the determined virtual domain. Tasks are received by virtual domains and assigned to worker threads, which can access a data structure specified for a given task.

Abstract: A table organized into a set of batch units is accessed. A set of N-grams are generated for a data value in the source table. The set of N-grams include a first N-gram of a first length and a second N-gram of a second length where the first N-gram corresponds to a prefix of the second N-gram. A set of fingerprints are generated for the data value based on the set of N-grams. The set of fingerprints include a first fingerprint generated based on the first N-gram and a second fingerprint generated based on the second N-gram and the first fingerprint. A pruning index that indexes distinct values in each column of the source table is generated based on the set of fingerprints and stored in a database with an association with the source table.

Abstract: A table organized into a set of batch units is accessed. A set of N-grams are generated for a data value in the source table. The set of N-grams include a first N-gram of a first length and a second N-gram of a second length where the first N-gram corresponds to a prefix of the second N-gram. A set of fingerprints are generated for the data value based on the set of N-grams. The set of fingerprints include a first fingerprint generated based on the first N-gram and a second fingerprint generated based on the second N-gram and the first fingerprint. A pruning index that indexes distinct values in each column of the source table is generated based on the set of fingerprints and stored in a database with an association with the source table.

Abstract: A table organized into a set of batch units is accessed. A set of N-grams are generated for a data value in the source table. The set of N-grams include a first N-gram of a first length and a second N-gram of a second length where the first N-gram corresponds to a prefix of the second N-gram. A set of fingerprints are generated for the data value based on the set of N-grams. The set of fingerprints include a first fingerprint generated based on the first N-gram and a second fingerprint generated based on the second N-gram and the first fingerprint. A pruning index that indexes distinct values in each column of the source table is generated based on the set of fingerprints and stored in a database with an association with the source table.

Abstract: A table organized into a set of batch units is accessed. A set of N-grams are generated for a data value in the source table. The set of N-grams include a first N-gram of a first length and a second N-gram of a second length where the first N-gram corresponds to a prefix of the second N-gram. A set of fingerprints are generated for the data value based on the set of N-grams. The set of fingerprints include a first fingerprint generated based on the first N-gram and a second fingerprint generated based on the second N-gram and the first fingerprint. A pruning index that indexes distinct values in each column of the source table is generated based on the set of fingerprints and stored in a database with an association with the source table.

Abstract: A query directed at a table organized into a set of batch units is received. The query comprises a predicate for which values are unknown prior to runtime. A set of values for the predicate are determined based on the query. An index access plan is created based on the set of values. Based on the index access plan, the set of batch units are pruned using a pruning index associated with the table. The pruning index comprises a set of filters that index distinct values in each column of the table. The pruning of the set of batch units comprises identifying a subset of batch units to scan for data that satisfies the query. The subset of batch units of the table are scanned to identify data that satisfies the query.

Abstract: 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.