Abstract: Joining data using a disjunctive operator is described. An example computer-implemented method can include receiving a query that includes a first disjunctive predicate involving a first table and a second table. The method may also include determining a first set of rows from the first table and generating a filter from the first set of rows. The method may also further include applying the filter to the second table to generate a second set of rows. Additionally, the method may also include joining the first set of rows and the second set of rows using a first disjunctive operator of the first disjunctive predicate to generate a first results set.

Abstract: In one aspect, a computer-implemented method includes detecting, by a server includes one or more processors, a request to perform a hash join operation on a data structure stored in a data storage device, forming a hash lookup dictionary based on lookup results in a hash table, storing the hash lookup dictionary in a cache, and probing, during a probing phase of the hash join operation, the cache.

Abstract: Systems, methods, and devices, for managing data skew during a join operation are disclosed. A method includes computing a hash value for a join operation and detecting data skew on a probe side of the join operation at a runtime of the join operation using a lightweight sketch data structure. The method includes identifying a frequent probe-side join key on the probe side of the join operation during a probe phase of the join operation. The method includes identifying a frequent build-side row having a build-side join key corresponding with the frequent probe-side join key. The method includes asynchronously distributing the frequent build-side row to one or more remote servers.

Abstract: Systems, methods, and devices, for managing data skew during a join operation are disclosed. A method includes computing a hash value for a join operation and detecting data skew on a probe side of the join operation at a runtime of the join operation using a lightweight sketch data structure. The method includes identifying a frequent probe-side join key on the probe side of the join operation during a probe phase of the join operation. The method includes identifying a frequent build-side row having a build-side join key corresponding with the frequent probe-side join key. The method includes asynchronously distributing the frequent build-side row to one or more remote servers.

Abstract: Systems, methods, and devices, for managing data skew during a join operation are disclosed. A method includes computing a hash value for a join operation and detecting data skew on a probe side of the join operation at a runtime of the join operation using a lightweight sketch data structure. The method includes identifying a frequent probe-side join key on the probe side of the join operation during a probe phase of the join operation. The method includes identifying a frequent build-side row having a build-side join key corresponding with the frequent probe-side join key. The method includes asynchronously distributing the frequent build-side row to one or more remote servers.

Abstract: Systems, methods, and devices, for managing data skew during a join operation are disclosed. A method includes computing a hash value for a join operation and detecting data skew on a probe side of the join operation at a runtime of the join operation using a lightweight sketch data structure. The method includes identifying a frequent probe-side join key on the probe side of the join operation during a probe phase of the join operation. The method includes identifying a frequent build-side row having a build-side join key corresponding with the frequent probe-side join key. The method includes asynchronously distributing the frequent build-side row to one or more remote servers.

Abstract: Systems, methods, and devices, for managing data skew during a join operation are disclosed. A method includes computing a hash value for a join operation and detecting data skew on a probe side of the join operation at a runtime of the join operation using a lightweight sketch data structure. The method includes identifying a frequent probe-side join key on the probe side of the join operation during a probe phase of the join operation. The method includes identifying a frequent build-side row having a build-side join key corresponding with the frequent probe-side join key. The method includes asynchronously distributing the frequent build-side row to one or more remote servers.

Abstract: Joining data using a disjunctive operator is described. An example computer-implemented method can include receiving a query that includes a first disjunctive predicate involving a first table and a second table. The method may also include determining a first set of rows from the first table and generating a filter from the first set of rows. The method may also further include applying the filter to the second table to generate a second set of rows. Additionally, the method may also include joining the first set of rows and the second set of rows using a first disjunctive operator of the first disjunctive predicate to generate a first results set.

Abstract: The subject technology receives a query plan, the query plan comprising a set of query operations, the set of query operations including at least one aggregation and a join operation, the join operation including a build side and a probe side. The subject technology inserts an aggregation operator below the probe side of the join operation. The subject technology causes the build side of the join operation to generate a hash table. The subject technology causes the build side of the join operation to generate a bloom filter based at least in part on the hash table and provide information, corresponding to properties of the build side, to a bloom filter. Based at least in part on the information, the subject technology determines at least one property of the join operation to determine whether to switch the aggregation operator to a pass through mode.

Abstract: Joining data using a disjunctive operator is described. An example computer-implemented method can include receiving a query that includes a first disjunctive predicate involving a first table and a second table. The method may also include determining a first set of rows from the first table and generating a filter from the first set of rows. The method may also further include applying the filter to the second table to generate a second set of rows. Additionally, the method may also include joining the first set of rows and the second set of rows using a first disjunctive operator of the first disjunctive predicate to generate a first results set.

Abstract: Joining data using a disjunctive operator using a lookup table is described. An example computer-implemented method can include receiving a query with a set of conjunctive predicates and a set of disjunctive predicates. The method may also include generating a lookup table for each predicate in the sets of conjunctive predicates and disjunctive predicates. The method, for each row in a probe-side table, may also further include looking up a value associated with that row in each of the lookup tables and adding the row to a results set when there is a match. Additionally, the method may also include returning the results set.

Abstract: The subject technology receives a query plan, the query plan comprising a set of query operations, the set of query operations including at least one aggregation. The subject technology analyzes the at least one aggregation to generate a modified query plan, the modified query plan including at least a top aggregation operator, an intermediate aggregation operator, and a bottom aggregation operator. The subject technology performs, with respect to the intermediate aggregation operator, at least one operation comprising: the subject technology receives an input intermediate data type; the subject technology performs an internalize operation on the input intermediate data type to generate an internal state; the subject technology performs an accumulate operation on the internal state to generate intermediate data; and the subject technology performs an externalize operation on the intermediate data to generate an output data type.

Abstract: Data in a micro-partition of a table is stored in a compressed form. In response to a database query on the table comprising a filter, the portion of the data on which the filter operates is decompressed, without decompressing other portions of the data. Using the filter on the decompressed portion of the data, the portions of the data that are responsive to the filter are determined and decompressed. The responsive data is returned in response to the database query. When a query is run on a table that is compressed using dictionary compression, the uncompressed data may be returned along with the dictionary look-up values. The recipient of the data may use the dictionary look-up values for memoization, reducing the amount of computation required to process the returned data.

Abstract: The subject technology provides information, corresponding to properties of a build side of a join operation, to a bloom filter. The subject technology, based at least in part on the information from the bloom filter, determines, during executing of a query plan, at least one property of the join operation to determine whether to switch an aggregation operator to a pass through mode, the at least one property comprising at least a reduction rate. The subject technology, switches, in response to the reduction rate being below a threshold value, the aggregation operator to the pass through mode during runtime of the query plan and, while the aggregation operator is in the pass through mode, an input stream of data goes through the aggregation operator without being analyzed and the input stream of data matches an output stream of data flowing out of the aggregation operator.

Abstract: Systems, methods, and devices, for managing data skew during a join operation are disclosed. A method includes computing a hash value for a join operation and detecting data skew on a probe side of the join operation at a runtime of the join operation using a lightweight sketch data structure. The method includes identifying a frequent probe-side join key on the probe side of the join operation during a probe phase of the join operation. The method includes identifying a frequent build-side row having a build-side join key corresponding with the frequent probe-side join key. The method includes asynchronously distributing the frequent build-side row to one or more remote servers.

Abstract: The subject technology receives a query plan, the query plan comprising a set of query operations, the set of query operations including at least one aggregation and at least one join operation. The subject technology analyzes the query plan to identify an aggregation that is redundant. The subject technology removes the aggregation based at least in part on the analyzing. The subject technology determines at least one aggregation property corresponding to at least one query operation of the query plan. The subject technology inserts at least one adaptive aggregation operator in the query plan based at least in part on the at least one aggregation property, the at least one aggregation property comprising a set of aggregation properties. The subject technology provides a modified query plan based at least in part on the inserted at least one adaptive aggregation operator in the query plan.

Abstract: Joining data using a disjunctive operator using a lookup table is described. An example computer-implemented method can include receiving a query with a set of conjunctive predicates and a set of disjunctive predicates. The method may also include generating a lookup table for each predicate in the sets of conjunctive predicates and disjunctive predicates. The method, for each row in a probe-side table, may also further include looking up a value associated with that row in each of the lookup tables and adding the row to a results set when there is a match. Additionally, the method may also include returning the results set.

Abstract: Lipase enzymes and methods of using the lipases in a baking for improving the volume, stability, tolerance of a baked product and/or reducing and reducing or eliminating the use of DATEM.

Abstract: The subject technology receives a query plan, the query plan comprising a set of query operations, the set of query operations including at least one aggregation and at least one join operation. The subject technology analyzes the query plan to identify an aggregation that is redundant. The subject technology removes the aggregation based at least in part on the analyzing. The subject technology determines at least one aggregation property corresponding to at least one query operation of the query plan. The subject technology inserts at least one adaptive aggregation operator in the query plan based at least in part on the at least one aggregation property. The subject technology provides a modified query plan based at least in part on the inserted at least one adaptive aggregation operator in the query plan.

Abstract: Systems, methods, and devices, for managing data skew during a join operation are disclosed. A method includes computing a hash value for a join operation and detecting data skew on a probe side of the join operation at a runtime of the join operation using a lightweight sketch data structure. The method includes identifying a frequent probe-side join key on the probe side of the join operation during a probe phase of the join operation. The method includes identifying a frequent build-side row having a build-side join key corresponding with the frequent probe-side join key. The method includes asynchronously distributing the frequent build-side row to one or more remote servers.