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New OLAP Aggregate Functions In DB2 for i, Part 1 - IT Jungle

7/12/2016 · The new OLAP aggregate functions differ from normal aggregate functions (such as MIN, MAX, SUM, and AVG) in that they can only be used in conjunction with an OLAP aggregation specification (OAS); whereas the normal aggregates can be used with or without an OAS (e.g., they can be used in a GROUP BY summary query).

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Efficient Processing of Ad-Hoc Top-k Aggregate Queries in OLAP

new query plans, compared with the traditional approach. 1 Introduction Aggregation is a key operation in data warehousing for OLAP (On-Line Analytical Processing), which is very im-portantfor decision support in a variety of applications such as manufacturing, sales management, stock analysis, etc. In

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Aggregate (data warehouse) - Wikipedia

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The aggregate navigation essentially examines the query to see if it can be answered using a smaller, aggregate table. Implementations of aggregate navigators can be found in a range of technologies: OLAP engines; Materialized views; Relational OLAP services; BI application servers or query tools

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Online analytical processing - Wikipedia

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Online analytical processing, or OLAP (/ ˈ oʊ l æ p /), is an approach to answer multi-dimensional analytical (MDA) queries swiftly in computing. OLAP is part of the broader category of business intelligence, which also encompasses relational databases, report writing and data mining. Typical applications of OLAP include business reporting for sales, marketing, management reporting ...

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Evaluation of Top-k OLAP Queries Using Aggregate R–trees

A top-k OLAP query groups measures with respect to some abstrac-tion level of interesting dimensions and selects the k groups with the highest aggregate value. An example of such a query is "find the 10 combinations of product-type and month with the largest sum of sales". Such queries may also be applied in a spatial database context, where objects are augmented .

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Compressed Data Cubes for OLAP Aggregate Query ...

OLAP, data cubes, clustering, density estimation, approximate query answering, data mining. 1. INTRODUCTION There has been much work on answering multi-dimensional aggregate queries efficiently, for example the data cube operator [13]. OLAP systems perform queries fast by pre-computing all or part of the data cube [15]. Such pre-computation ...

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Aggregate Queries in Peer-to-Peer OLAP

mally, a P2P-OLAP query over this data model, is a query involving aggregate functions, defined over generalizations of fact tables and dimensions that are distributed in a P2P network. We characterize P2P OLAP queries as a set of datalog rules with aggregation. Based on this characteriza-103 . tion, we discuss an evaluation procedure for these queries. Whenever a query is submitted to a node ...

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(PDF) Aggregate queries in peer-to-peer OLAP

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OLAP query execution costs many minutes by its enormous data and OLAP query properties. On the other hand, MOLAP has fast responses. But it has a physical space limit to materialize all cells in ...

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Evaluation of Top-k OLAP Queries Using Aggregate R–Trees

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A top-k OLAP query groups measures with respect to some abstrac-tion level of interesting dimensions and selects the k groups with the highest aggregate value. An example of such a query is "find the 10 combinations of product-type and month with the largest sum of sales". Such queries may also

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The Rise and Fall of the OLAP Cube | by Huy .

The queries in the latter category aggregate data across many more elements when compared to the queries for the former. In our example of a car dealership, you might be able to get a way with running both OLTP and OLAP query-types on a normal relational database. But if you deal with huge amounts of data — if you're querying a global database of car sales over the past .

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What is an Aggregate? OLAP Aggregate Definition

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Aggregation or consolidation involves computing all of these data relationships for one or more dimensions, for example, adding up all Departments to get Total Department data. It has been claimed that for complex queries OLAP Cubes can produce an answer in about 0.1% of the time for the same query on OLTP relational data.

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Providing Probabilistically-Bounded Approximate Answers to ...

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query answering techniques in OLAP: scalability, i.e. the capability of the techniques of scaling as input data cubes grow in size, and accuracy, i.e. the need for guarantees on the degree of approximation of the retrieved answers. Specifically, our techniques presented in [9] are tailored for OLAP aggregate

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OLAP window aggregate functions - IBM

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These aggregate functions do not require an OLAP window to calculate aggregate values from a query result set. They behave like OLAP window aggregation functions, however, in calling contexts where the OVER clause in the function expression defines one or more window partitions, or includes the window ORDER clause and the window Frame clause.

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Aggregate (MDX) - iccube

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Aggregate - SUM aggregation, same tuple Aggregation over the same tuple is going to add twice the value. Note, we are adding twice the same fact row which is .

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Compressed data cubes for OLAP aggregate .

Compressed data cubes for OLAP aggregate query approximation on continuous dimensions. Applied computing. Operations research. Decision analysis. Information systems. Data management systems. Database management system engines. Database query processing. Information retrieval. Information retrieval query processing . Retrieval tasks and goals. Clustering and classification. Information .

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Metric Parameter for Aggregate Queries (OLAP) .

Doradus is a REST service that extends a Cassandra NoSQL database with a graph-based data model, advanced indexing and search features, and a REST API. See also doradus-openshift-quickstart, which allows Doradus to run as an OpenShift cartridge! - QSFT/Doradus

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OBIEE - How to define OBIEE to leverage SQL .

What's Different Configuring OBI EE to Query Cube Views ? The Aggregation Measures While not really different from any other implementation, it is useful to point out that it is very likely that cube views will contain measures such as rankings and percentages that should generally not be aggregated in SQL. The cube will calculate these measures at summary levels and aggregation should be ...

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OLAP – Runtime Aggregation vs.

1/31/2013 · OLAP – Runtime Aggregation vs. Pre-aggregation Aggregate at runtime Pre-aggregate Most flexible Fast Fast – scatter gather Efficient – O(1) Space efficient High throughput But But I/O, CPU intensive More effort to process (latency) slow for larger data Combinatorial explosion (space) low throughput No flexibility© 2012 Adobe Systems .

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Efficient Processing of Ad-Hoc Top-k Aggregate Queries in OLAP

new query plans, compared with the traditional approach. 1 Introduction Aggregation is a key operation in data warehousing for OLAP (On-Line Analytical Processing), which is very im-portantfor decision support in a variety of applications such as manufacturing, sales management, stock analysis, etc. In

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Overview of OLAP cubes for advanced analytics | .

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A common OLAP cube query, for example, sums up the total time for all activities that are In Progress. Other common aggregation functions include Min, Max, and Count. After the raw data has been processed in an OLAP cube, users can perform more complex calculations and queries using multidimensional expressions (MDX) to define their own measure expressions or calculated members.

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Aggregate Query Commands (OLAP) · .

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Doradus is a REST service that extends a Cassandra NoSQL database with a graph-based data model, advanced indexing and search features, and a REST API. See also doradus-openshift-quickstart, which allows Doradus to run as an OpenShift cartridge! - QSFT/Doradus

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