Abstract: Various embodiments for a disk-based merge for combining merged hash maps are described herein. An embodiment operates by identifying a first hash map and a second hash map, and comparing a first hash value from the first hash map with a second hash value from the second hash map, with the lowest index values. A lowest hash value is identified based on the comparison, and an entry corresponding to the lowest hash value is stored in a combined hash map. This process is repeated until all of the hash values from both the first set of hash values and the second set of hash values are stored in the combined hash map. A query is received, and processed based on the combined hash map.

Abstract: Various embodiments for a disk-based merge for hash maps are described herein. An embodiment operates by identifying a plurality of hash maps with a plurality of disjunctions, ordering the one or more entries in each disjunction based on the hash value, and assigning an index value to each data value based on the ordering. The hash values of each of the entries may be moved to memory and compared for a particular disjunction. A data value with a lower hash value as determined based on the comparison is selected and stored in a merged hash map. The process is repeated until all the data values have been compared. A query is received, and processed based on the merged hash map.

Abstract: Various embodiments for a disk-based merge for combining merged hash maps are described herein. An embodiment operates by identifying a first hash map and a second hash map, and comparing a first hash value from the first hash map with a second hash value from the second hash map, with the lowest index values. A lowest hash value is identified based on the comparison, and an entry corresponding to the lowest hash value is stored in a combined hash map. This process is repeated until all of the hash values from both the first set of hash values and the second set of hash values are stored in the combined hash map. A query is received, and processed based on the combined hash map.

Abstract: Various embodiments for a disk-based merge for hash maps are described herein. An embodiment operates by identifying a plurality of hash maps with a plurality of disjunctions. The hash values of each of the entries may be moved to memory and compared for a particular disjunction. A data value with a lower hash value as determined based on the comparison is selected and stored in a merged hash map. The process is repeated until all the data values have been compared. A query is received, and processed based on the merged hash map.

Abstract: Various embodiments for a disk-based merge for hash maps are described herein. An embodiment operates by identifying a plurality of hash maps with a plurality of disjunctions, ordering the one or more entries in each disjunction based on the hash value, and assigning an index value to each data value based on the ordering. The hash values of each of the entries may be moved to memory and compared for a particular disjunction. A data value with a lower hash value as determined based on the comparison is selected and stored in a merged hash map. The process is repeated until all the data values have been compared. A query is received, and processed based on the merged hash map.

Abstract: Various embodiments for a disk-based merge for combining merged hash maps are described herein. An embodiment operates by identifying a first hash map and a second hash map, and comparing a first hash value from the first hash map with a second hash value from the second hash map, with the lowest index values. A lowest hash value is identified based on the comparison, and an entry corresponding to the lowest hash value is stored in a combined hash map. This process is repeated until all of the hash values from both the first set of hash values and the second set of hash values are stored in the combined hash map. A query is received, and processed based on the combined hash map.

Abstract: Embodiments are described for a database management system comprising a memory and at least one processor coupled to the memory. The at least one processor is configured to receive a plurality of queries and determine a first identifier based on the plurality of queries. The at least one processor is further configured to create a first bloom filter based on the first identifier and receive an additional query corresponding to the first identifier. The at least one processor is further configured to execute the first bloom filter.

Abstract: Embodiments are described for a database management system comprising a memory and at least one processor coupled to the memory. The at least one processor is configured to receive a query that corresponds to a data slice and determine a bloom filter based on the query. The at least one processor is further configured to determine that the data slice includes data requested by the query based on the bloom filter and in response to determining that the data slice includes the data requested by the query, load the data slice to the memory.

Abstract: Various embodiments for a data compression store and search system are described herein. An embodiment operates by receiving a query to search a plurality of documents. It is determined that the plurality of documents are stored in a compressed format comprising a plurality of shells and a plurality of snippets. A first snippet that includes the query identifier is identified, and a first shell including a reference to the first snippet is identified. A readable version of a first document of the plurality of documents is assembled from the first shell. The assembled readable version of the first document is provided responsive to the query.

Abstract: Various embodiments for a data compression store and search system are described herein. An embodiment operates by receiving a query to search a plurality of documents. It is determined that the plurality of documents are stored in a compressed format comprising a plurality of shells and a plurality of snippets. A first snippet that includes the query identifier is identified, and a first shell including a reference to the first snippet is identified. A readable version of a first document of the plurality of documents is assembled from the first shell. The assembled readable version of the first document is provided responsive to the query.

Abstract: Various embodiments for a data compression store and search system are described herein. An embodiment operates by receiving a query to search a plurality of documents. It is determined that the plurality of documents are stored in a compressed format comprising a plurality of shells and a plurality of snippets. A first snippet that includes the query identifier is identified, and a first shell including a reference to the first snippet is identified. A readable version of a first document of the plurality of documents is assembled from the first shell. The assembled readable version of the first document is provided responsive to the query.

Abstract: A system includes reception of a query specifying a database table, an aggregate function, a plurality of grouping columns and an aggregation column, determination of whether a tuple of a first row of the grouping columns in the database tables is unique in the grouping columns, storage, if it is determined that the tuple of the first row of the grouping columns is unique in the grouping columns, of a result set entry including the tuple and an aggregation value determined based on a value of the aggregation column in the first row, and, if it is determined that the tuple of the first row of the grouping columns is not unique in the grouping columns, determination of a key based on the tuple and performance of a hash lookup using the key.

Abstract: A system includes reception of a query specifying a database table, an aggregate function, a plurality of grouping columns and an aggregation column, determination of whether a tuple of a first row of the grouping columns in the database tables is unique in the grouping columns, storage, if it is determined that the tuple of the first row of the grouping columns is unique in the grouping columns, of a result set entry including the tuple and an aggregation value determined based on a value of the aggregation column in the first row, and, if it is determined that the tuple of the first row of the grouping columns is not unique in the grouping columns, determination of a key based on the tuple and performance of a hash lookup using the key.

Abstract: In one aspect, there is provided a method. The method may include adding a tuple phrase to a phrase index as part of a lazy creation of the phrase index. The adding may include adding the tuple phrase to a dictionary mapped to the phrase index, adding to the phrase index a document identifier and a positional information for the tuple phrase, and adapting a first threshold and a second threshold value, the first threshold representing a threshold lower estimate of query processing burden associated with a least burdensome tuple phrase in the dictionary and the second threshold representing a top estimate of query processing burden associated with a most burdensome tuple phrase in the dictionary. The method may further include sending a query response including a generated query result corresponding to the tuple phrase.

Abstract: A method, a system and a computer program product for execution of queries. A first query is executed using a first query execution plan to generate a first result data by applying a first query operator to a first data stored in a first storage location. The first result data is provided to a second query execution plan for execution of a second query. The second query is executed on a second data stored in a second storage location in accordance with the second query execution plan. The second query execution plan includes a second query operator. Based on the execution of the second query, a second result data is generated in accordance with the second query execution plan by at least applying the second query operator to at least the provided first result data.

Abstract: The present disclosure involves systems, software, and computer implemented methods for compression operation combining duplicate index entries independent of a data model. One example method includes operations to identify an update to at least one entry in a compressed index that includes a plurality of entries, each associated with a unique entry ID. An entry ID of each entry associated with the update are identified. A self-update is performed for each entry not associated with the entry IDs associated with the update, which comprises inserting a value associated with those non-updated entries to an uncompressed index in connection with that entry's corresponding entry ID. For each entry associated with the update, a particular update value from the identified update is inserted into the uncompressed index associated with the particular entry ID. When completed, the uncompressed index is compressed into a new version of the compressed index.

Abstract: In one aspect, there is provided a method. The method may include adding a tuple phrase to a phrase index as part of a lazy creation of the phrase index. The adding may include adding the tuple phrase to a dictionary mapped to the phrase index, adding to the phrase index a document identifier and a positional information for the tuple phrase, and adapting a first threshold and a second threshold value, the first threshold representing a threshold lower estimate of query processing burden associated with a least burdensome tuple phrase in the dictionary and the second threshold representing a top estimate of query processing burden associated with a most burdensome tuple phrase in the dictionary. The method may further include sending a query response including a generated query result corresponding to the tuple phrase.

Abstract: A method, a system and a computer program product for execution of queries. A first query is executed using a first query execution plan to generate a first result data by applying a first query operator to a first data stored in a first storage location. The first result data is provided to a second query execution plan for execution of a second query. The second query is executed on a second data stored in a second storage location in accordance with the second query execution plan. The second query execution plan includes a second query operator. Based on the execution of the second query, a second result data is generated in accordance with the second query execution plan by at least applying the second query operator to at least the provided first result data.

Abstract: In one respect, there is provided a method. The method can include processing a first data chunk to generate a first intermediate result. A key map can be generated based on a determination that a quantity of the key-value pairs in the first intermediate result exceeds a threshold. The key map can be generated to include keys in the first intermediate result. A second data chunk can be processed to generate a second intermediate result. The second data chunk can be processed based on the key map. The processing of the second data chunk can include omitting a key-value pair in the second data chunk from being inserted into the second intermediate result based on a key associated with the key-value pair being absent from the key map. A preview of the processing of the dataset can be generated based on the first intermediate result and the second intermediate result.

Abstract: A method can include: reordering an enriched inverted index associated with a database, the enriched inverted index including a first inverted list having a first plurality of current document identifiers of records that contain a first data value, the enriched inverted index further including a first data structure storing enrichment data, the reordering of the enriched inverted index comprising: generating an ordinal sequence corresponding to an order of a first plurality of current document identifiers that include a change of at least one of the first plurality of current document identifiers to a new document identifier; determining a reordered ordinal sequence corresponding to a sorted order of the second plurality of document identifiers; separately reordering, based at least on the reordered ordinal sequence, the first plurality of current document identifiers in the first inverted list and the enrichment data in the first data structure.