A unified access layer (UAL) and scalable query engine receive queries from various interfaces and executes the queries with respect to non-heterogeneous data management and analytic computing platforms that are sources of record for data they store. Query performance is monitored and used to generate a query performance model. The query performance model may be used to generate alternatives for queries of users or groups of users or to generate policies for achieving a target performance. Performance may be improved by monitoring queries and retrieving catalog data for databases referenced and generating a recommendation model according to them. Duplicative or overlapping sources may be identified based on the monitoring and transformations to improve accuracy and security may be suggested. A recommendation model may be generated based on analysis of queries received through the UAL. Transformations may be performed according to the recommendation model in order to improve performance.

A unified access layer (UAL) and scalable query engine receive queries from various interfaces and executes the queries with respect to non-heterogeneous data management and analytic computing platforms that are sources of record for data they store. Query performance is monitored and used to generate a query performance model. The query performance model may be used to generate alternatives for queries of users or groups of users or to generate policies for achieving a target performance. Performance may be improved by monitoring queries and retrieving catalog data for databases referenced and generating a recommendation model according to them. Duplicative or overlapping sources may be identified based on the monitoring and transformations to improve accuracy and security may be suggested. A recommendation model may be generated based on analysis of queries received through the UAL. Transformations may be performed according to the recommendation model in order to improve performance.

A unified access layer (UAL) and scalable query engine receive queries from various interfaces and executes the queries with respect to non-heterogeneous data management and analytic computing platforms that are sources of record for data they store. Query performance is monitored and used to generate a query performance model. The query performance model may be used to generate alternatives for queries of users or groups of users or to generate policies for achieving a target performance. Performance may be improved by monitoring queries and retrieving catalog data for databases referenced and generating a recommendation model according to them. Duplicative or overlapping sources may be identified based on the monitoring and transformations to improve accuracy and security may be suggested. A recommendation model may be generated based on analysis of queries received through the UAL. Transformations may be performed according to the recommendation model in order to improve performance.

The present teaching relates to a method, system and programming for searching a data storage. A key is extracted from a request and a metadata object associated with the key is identified. Further, a determination is made as to whether the metadata object is associated with a data structure stored in a first portion of the data storage. In response to a successful determination, the data structure is searched to retrieve a value associated with the key from the first portion. In response to an unsuccessful determination, a cache is searched to retrieve the value associated with the key, and in response to the key being absent in the cache, a file associated with the metadata object is searched to retrieve the value associated with the key, wherein the file is stored in a second portion of the data storage.

This disclosure provides various techniques that may allow for accessing values stored in a data structure that stores multiple values corresponding to database transactions using a skip list. A key may be used to traverse the skip list to access data associated with the key. The skip list maintains on ordering of multiple keys, each associated with a particular record in the data structure, using indirect links between data records in the data structure that reference buckets included in hash table. Each bucket includes pointers to one or more records in the skip list.

Embodiments including methods and apparatus to share file and file recommendations are disclosed. Data is received indicating a particular media item from a first service provider, where the particular media item is accessible from the first service provider according to a first pointer. A second pointer is identified in a database according to which the particular media item is accessible from a second service provider. Data indicating the second pointer is transmitted to a media playback system, via at least one of a WAN or a LAN.

This disclosure provides various techniques that may allow for accessing values stored in a data structure that stores multiple values corresponding to database transactions using a skip list. A key may be used to traverse the skip list to access data associated with the key. The skip list maintains on ordering of multiple keys, each associated with a particular record in the data structure, using indirect links between data records in the data structure that reference buckets included in hash table. Each bucket includes pointers to one or more records in the skip list.

A network element includes a data structure, a cache memory and circuitry. The data structure is configured to store multiple rules specifying processing of packets received from a communication network. The cache memory is configured to cache multiple rules including a subset of the rules stored in the data structure. Each rule that is cached in the cache memory has a respective cost value corresponding to a cost of retrieving the rule from the data structure. The circuitry is configured to receive one or more packets from the communication network, to process the received packets in accordance with one or more of the rules, by retrieving the rules from the cache memory when available, or from the data structure otherwise, to select a rule to be evicted from the cache memory, based on one or more respective cost values of the rules currently cached, and to evict the selected rule.

Techniques are described for encoding join columns that belong to the same domain with a common dictionary. The tables are encoded with dictionary indexes that make the comparison operation of a join query a quick equality check of two integers and there is no need to compute any hashes during execution. Additionally, the techniques described herein minimize the bloom filter creation and evaluation cost as well because the dictionary indexes serve as hash values into the bloom filter. If the bloom filter is as large as the range of dictionary indexes, then the filter is no longer a probabilistic structure and can be used to filter rows in the probe phase with full certainty without any significant overhead.

In general, embodiments of the technology relates to a method for attaching a detachable library. The method includes obtaining a detachable library, wherein the detachable library comprises a plurality of data files and each of the data files comprises a library scope identifier (ID), and where the library scope IDs are unique within the detachable library and reattaching the detachable library to a database. The method further includes assigning a node scope ID to each of the data files in the detachable library, where the node scope IDs are unique within the database, creating a mapping index using the node scope IDs and the library scope IDs, and processing a request from a client using the mapping index, where the request includes a library scope ID.