Abstract: Systems and methods for enhancing security during access and retrieval of data with multi-cloud storage are disclosed. A method includes: receiving, by a computing device, data to be stored in a distributed computing environment; compressing, by the computing device, the received data; shredding, by the computing device, the compressed data into a plurality of data chunks; storing, by the computing device, the plurality of data chunks in a plurality of locations in the distributed computing environment; generating, by the computing device, a metadata file including a mapping of each of the plurality of data chunks and a corresponding location of the plurality of locations in the distributed computing environment in which the data chunk is stored; shredding, by the computing device, the metadata file into a plurality of file chunks; and storing, by the computing device, the plurality of file chunks in the distributed computing environment.

Abstract: Systems and methods for enhancing security during access and retrieval of data with multi-cloud storage are disclosed. A method includes: receiving, by a computing device, data to be stored in a distributed computing environment; compressing, by the computing device, the received data; shredding, by the computing device, the compressed data into a plurality of data chunks; storing, by the computing device, the plurality of data chunks in a plurality of locations in the distributed computing environment; generating, by the computing device, a metadata file including a mapping of each of the plurality of data chunks and a corresponding location of the plurality of locations in the distributed computing environment in which the data chunk is stored; shredding, by the computing device, the metadata file into a plurality of file chunks; and storing, by the computing device, the plurality of file chunks in the distributed computing environment.

Abstract: In one embodiment, a method for improving cardinality estimation of a join predicate between a fact table and an overloaded dimension table is provided. The method includes receiving a dimension table and a fact table in a join predicate of one or more SQL statements. The method further includes identifying a majority of records in the fact table that refer to a subset of records in the dimension table. The method further includes computing a filter factor of the join predicate between the dimension table and the fact table. The method further includes creating a statistical view using one or more relevant portions of the dimension table that are referred to by the fact table.

Abstract: In one embodiment, a method for improving cardinality estimation of a join predicate between a fact table and an overloaded dimension table is provided. The method includes receiving a dimension table and a fact table in a join predicate of one or more SQL statements. The method further includes identifying a majority of records in the fact table that refer to a subset of records in the dimension table. The method further includes computing a filter factor of the join predicate between the dimension table and the fact table. The method further includes creating a statistical view using one or more relevant portions of the dimension table that are referred to by the fact table.

Abstract: In one embodiment, a method for improving cardinality estimation of a join predicate between a fact table and an overloaded dimension table is provided. The method includes receiving a dimension table and a fact table in a join predicate of one or more SQL statements. The method further includes identifying a majority of records in the fact table that refer to a subset of records in the dimension table. The method further includes computing a filter factor of the join predicate between the dimension table and the fact table. The method further includes creating a statistical view using one or more relevant portions of the dimension table that are referred to by the fact table.

Abstract: In one embodiment, a method for improving cardinality estimation of a join predicate between a fact table and an overloaded dimension table is provided. The method includes receiving a dimension table and a fact table in a join predicate of one or more SQL statements. The method further includes identifying a majority of records in the fact table that refer to a subset of records in the dimension table. The method further includes computing a filter factor of the join predicate between the dimension table and the fact table. The method further includes creating a statistical view using one or more relevant portions of the dimension table that are referred to by the fact table.

Abstract: In one embodiment, a method for improving cardinality estimation of a join predicate between a fact table and an overloaded dimension table is provided. The method includes receiving a dimension table and a fact table in a join predicate of one or more SQL statements. The method further includes identifying a majority of records in the fact table that refer to a subset of records in the dimension table. The method further includes computing a filter factor of the join predicate between the dimension table and the fact table. The method further includes creating a statistical view using one or more relevant portions of the dimension table that are referred to by the fact table.

Abstract: In one embodiment, a method for improving cardinality estimation of a join predicate between a fact table and an overloaded dimension table is provided. The method includes receiving a dimension table and a fact table in a join predicate of one or more SQL statements. The method further includes identifying a majority of records in the fact table that refer to a subset of records in the dimension table. The method further includes computing a filter factor of the join predicate between the dimension table and the fact table. The method further includes creating a statistical view using one or more relevant portions of the dimension table that are referred to by the fact table.

Abstract: In one embodiment, a method for improving cardinality estimation of a join predicate between a fact table and an overloaded dimension table is provided. The method includes receiving a dimension table and a fact table in a join predicate of one or more SQL statements. The method further includes identifying a majority of records in the fact table that refer to a subset of records in the dimension table. The method further includes computing a filter factor of the join predicate between the dimension table and the fact table. The method further includes creating a statistical view using one or more relevant portions of the dimension table that are referred to by the fact table.

Abstract: In one embodiment, a method for improving cardinality estimation of a join predicate between a fact table and an overloaded dimension table is provided. The method includes receiving a dimension table and a fact table in a join predicate of one or more SQL statements. The method further includes identifying a majority of records in the fact table that refer to a subset of records in the dimension table. The method further includes computing a filter factor of the join predicate between the dimension table and the fact table. The method further includes creating a statistical view using one or more relevant portions of the dimension table that are referred to by the fact table.