Sap Se

Sap Ag

Nico Bohnsack

Kai Stammerjohann

Frederik Transier

Christian Bensberg

Christian Mathis

Andreas Amler

Till Merker

Paul Willems

Wolfgang Stephan

Manuel Mayr

Peter Sanders

Arnaud Lacurie

Stephan Kottler

Dennis Felsing

Ingo Müller

Arrangements for a reading scheme for column-oriented databases are provided. A virtual column may be generated by applying a structured query language operation on distinct values in a column of data in a table. Based on applying the structured query language operation, the virtual column may be populated with corresponding precalculated values. The virtual column may be compressed with dictionary-based compression. The compressing may include generating a column of value identifiers, each of the value identifiers representing a distinct value in the column of data. A database query against the compressed virtual column may be received. A result of the database query may be returned by retrieving one or more of the precalculated values from the compressed virtual column.

Calculated dictionary column readers

In an example embodiment, a specialized execution process for a Disk Group-By operator with at least one distinct or ordered aggregation is provided. This specialized execution process involves writing all linked lists to disk (optionally this is performed only if the memory budget is coming close to being surpassed). Initially, a separate disk partition can be created per group, but once a partition becomes too large a new partition for the group is created. A partition is considered too large if it would not be able to be loaded into memory without surpassing the memory budget. As a result, every group can have a list of one or more disk partitions attached to it. The data belonging to each group is sorted using a sorted merge from disk.

Disk group-by with sorted merge

A method may include inserting, into a hash trie, data records from a database table. The inserting may include traversing the hash trie to identify, for each data record included in the database table, a corresponding node at which to insert the data record. The hash trie may be traversed based on a hash of a key value associated with each data record. The node at which to insert a data record may be identified based on an offset forming a binary representation of the hash of a key value associated with that data record. The offset may include a portion of a plurality of binary digits forming the binary representation. A data record may be inserted at a corresponding node by updating a data structure included at the node. A database operation may be performed based on the hash trie filled with the data records from the database table.

Hash trie based optimization of database operations

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.

Preview data aggregation

A new dictionary can be created for a result column in a query plan operation executed on a database. The result column can be generated by multiple worker jobs running in parallel to read tasks from a shared queue as part of a query plan operation that includes a group-by column within an input set of input columns. The group-by column can include an original dictionary for all values contained within the group-by column If the new dictionary has fewer entries than the original dictionary for the group-by column such that mapping is required between old value identifiers within the group-by column and new value identifiers within the result column, the old value identifiers are renamed to the new value identifiers using a mapping vector.

Lock-free generation of columns with minimal dictionaries after parallel aggregation

According to some embodiments, a system and method for a parallel join of relational data tables may be provided by calculating, by a plurality of concurrently executing execution threads, hash values for join columns of a first input table and a second input table; storing the calculated hash values in a set of disjoint thread-local hash maps for each of the first input table and the second input table; merging the set of thread-local hash maps of the first input table, by a second plurality of execution threads operating concurrently, to produce a set of merged hash maps; comparing each entry of the merged hash maps to each entry of the set of thread-local hash maps for the second input table to determine whether there is a match, according to a join type; and generating an output table including matches as determined by the comparing.

Hash-join in parallel computation environments

A system, method and medium may provide determination of a first plurality of a plurality of data records assigned to a first processing unit, identification of a first record of the first plurality of data records, the first record associated with a first key value, generation of a first dictionary entry of a first dictionary for the first key value, storage of a first identifier of the first record as a tail identifier and as a head identifier in the first dictionary entry, storage an end flag in a first shared memory location, the first shared memory location associated with the first record, identification of a second record of the first plurality of data records, the second record associated with the first key value, replacement of the tail identifier in the first dictionary entry with a second identifier of the second record, and storage of the first identifier in a second shared memory location, the second shared memory location associated with the second record.

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Ingersleben, Germany

Nico Bohnsack