Methods, apparatus, and processor-readable storage media for implementing dual relationship-based hash structures for non-volatile memory technology are provided herein. An example computer-implemented method includes generating a hash storage structure by: creating multiple layers of storage components, wherein a first layers comprise a first number of storage components and at least a second layer comprises at least a second number of storage components less than the first number of storage components; configuring the at least a second layer to share at least a portion of the storage components therein with at least a portion of the storage components in the first layer; partitioning each of the storage components in each of the multiple layers into multiple portions; configuring a respective status value space for each of the multiple portions of each of the storage components in the multiple layers; and implementing the hash storage structure in at least one storage system.

The described implementations relate to processing of electronic data. One implementation is manifest as a technique that can include obtaining a relational query that references one or more data items and associating progress intervals with the data items. The technique can also include converting the relational query into a corresponding streaming query, and providing the streaming query and the data items with the progress intervals to a stream engine that produces incremental results of the query. For example, the progress intervals can be based on row numbers of a relational database table. The progress intervals can be used to define event lifetimes of streaming events that are provided as inputs to the stream engine.

In a distributed database, many nodes can store copies, or instances, of the same record. If the record is split on one node, it should be split on the other nodes to maintain consistency, concurrency, and correctness of the data in the distributed database. In some distributed databases, the records are locked during the update process to ensure data integrity. Unfortunately, locking the records can increase latency, especially for larger databases. But if the records aren't locked and a node fails as a record is being split and updated simultaneously, the split and update may not propagate throughout the distributed database, leading to a loss of data integrity. Exchanging messages about the status of record splitting and forwarding updates internally reduces the likelihood of a loss of data integrity due to a node failure.

Embodiments of systems and methods for a search system that is adapted to utilize a family search operator are disclosed. Such a family search operator may return all documents that match the inner expression encompassed by the family search operator or having a family member that matched the inner expression of the family search operator.

Techniques are provided for data filtering using hardware accelerators. An apparatus comprises a processor, a memory and a plurality of hardware accelerators. The processor is configured to stream data from the memory to a first one of the hardware accelerators and to receive filtered data from a second one of the hardware accelerators. The plurality of hardware accelerators are configured to filter the streamed data utilizing at least one bit vector partitioned across the plurality of hardware accelerators. The hardware accelerators may be field-programmable gate arrays.

A method, according to one embodiment, includes identifying data to be stored in one or more tables within a predetermined portion of a partitioned storage in one of a plurality of nodes, the predetermined portion having at least one replica, and where no two identical replicas reside on a single node; assigning an identifier and a data storage hierarchical level to the data; mapping the data to an index and storing the data in accordance with the index and the data storage hierarchical level, the storing including writing the data to a row in one of the one or more tables on the predetermined portion and recording a write operation into a transaction log of the node; receiving a plurality of write operations; and combining a plurality of write tasks of the predetermined portion for a predetermined time period.

According to examples, an apparatus may include a processor and a memory on which are stored machine-readable instructions that when executed by the processor cause the processor to receive parameters for a partition range for a partition key associated with a table. The table may have a vertical table structure. The processor may generate an index of vertical table columns based on the received parameters for the partition range. The generated index may be a physical store for data from the table and may have a subset of rows of the table correlating to the partition range. The processor may receive a query having a predicate associated with the partition key associated with the table and, based on a determination that the predicate included in the received query is within a partition range for the generated index, the processor may execute the query using the generated index.

A data exchange that provides historical data indexed by date is provided. The data exchange may include a raw data layer, a model data layer, a delta staging layer, a delta database and a plurality of workspaces. The raw data layer may be a landing zone for raw data records. The model data layer may include modeled data records. The delta staging layer may be a landing zone for changed data. The changed data may correspond to changes made to the data records. The delta database may be divided into partitions. Each partition may hold data records that changed during a given time period. A plurality of data records may be continuously transferred from the raw data layer to both the model data layer and the delta staging layer. Once, during a predetermined time period, the contents of the delta staging layer may replace the contents of a partition.

During a query compilation process, a query is received that is directed to a set of source tables, each source table from the set of source tables being organized into at least one micro-partition and the query including at least one pruning operation. During the query compilation process, a modification of the query is performed for adjusting the at least one pruning operation, the modification being based on a set of statistics collected for previous pruning operations on at least a portion of the set of source tables and a set of heuristics, the set of statistics indicating at least an amount of execution time for each previous query associated with each of the previous pruning operations. The query is compiled including the modification of the query. The compiled query is provided to an execution node of a database system for execution.

The present disclosure provides a multi-party data joint query method, a device, a server and a storage medium. The multi-party data joint query method executed by a manager includes: analyzing a multi-party joint query sentence to obtain a logical execution plan; processing the logical execution plan according to providers of respective nodes in the logical execution plan to obtain a physical execution plan of each provider; and generating a query instruction of each provider according to the physical execution plan of each provider, and sending the query instruction to respective provider. The query instruction is configured to instruct the providers to perform a query cooperatively.