Hiperspace.SQL 2.1.6

.NET 8.0 This package targets .NET 8.0. The package is compatible with this framework or higher. 
dotnet add package Hiperspace.SQL --version 2.1.6                

                    
                

            
NuGet\Install-Package Hiperspace.SQL -Version 2.1.6
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package. 
<PackageReference Include="Hiperspace.SQL" Version="2.1.6" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
paket add Hiperspace.SQL --version 2.1.6                

                    
                

            
#r "nuget: Hiperspace.SQL, 2.1.6"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package. 
// Install Hiperspace.SQL as a Cake Addin
#addin nuget:?package=Hiperspace.SQL&version=2.1.6

// Install Hiperspace.SQL as a Cake Tool
#tool nuget:?package=Hiperspace.SQL&version=2.1.6

Hiperspace.SQL

Hiperspace.SQL is a full SQL query engine for Hiperspace, supporting the full range of joins, aggregations, and subqueries.

Hiperspace.SQL provides the same query functionality as a .NET client can use with LINQ queries, but without the need to write code in C#/F#

Hiperspace fully supports point-in-time "time travel" queries that are not possible with Python Data-Frames or DuckDB

Features

  • Hiperspace.SQL is not limited to queries of columns within a table, but supports the full navigation of properties of Hiperspace elements
  • Where a column is a complex object it is returned as a JSON object
  • Executing a batch of SQL statements return columnar data frames (dictionary of column-name and array of values)
  • Explain SQL returns the execution plan, detailing the SetSPaces accessed and keys used for search (Key, Index, Scan)
  • The Parquet method returns a Parquet file that can be used with any Apache Parquet library, or added to DuckDB OLAP store

Data Dictionary

SCHEMA_TABLE

Column Name Data Type Description
TABLE_NAME string The name of the table
TABLE_TYPE string The type of the table in SCHEMA_PROPERTY

SCHEMA_COLUMN

Column Name Data Type Description
TABLE_NAME string The name of the table
COLUMN_NAME string The name of the column
COLUMN_TYPE string The type of the table in SCHEMA_PROPERTY

SCHEMA_PROPERTY

Column Name Data Type Description
TYPE_NAME string The Type Name
PROPERTY_NAME string The name of each property
PROPERTY_TYPE string reference to SCHEMA_PROPERTY.TYPE_NAME

Examples

Simple query

SELECT p.Name, p.Gender FROM Persons as p WHERE p.Name = 'Lucy'

Query parameters

SELECT p.Name, p.Gender FROM Persons as p WHERE p.Name = :name

Query batches

SELECT p.Name, p.Gender FROM Persons as p WHERE p.Name = :name;
SELECT Name as name, Father as father from   Persons ;

Joins

SELECT  p.Name, f.Name as Father, f.Father as GrandFather
FROM    Persons as p 
join    Persons as f on p.Father.Name = f.Name
WHERE   p.Name = :name

Aggregates

select  p.Father.Name, count(p.Name) as Children
from    Persons as p
group by p.Father.Name as f
having count(*) > 1;

Like expressions

select  p.Father.Name, count(p.Name) as Children
from    Persons as p
where   Name like 'L%' and Name like '%y' or (Name like '%u%' and Name like '_uc_')
group by p.Father.Name as f
having count(*) > 1;

Null handling

select  p.Name, p.Father.Name
from    Persons as p
where   Name is not null

in query

SELECT p.Name, p.Gender 
FROM Persons as p 
WHERE p.Gender in (select p2.Gender from Persons as p2 where p2.Name = 'Lucy')

union

SELECT p.Name, p.Gender 
FROM Persons as p 
WHERE p.Name in ('Lucy', 'Mark')
union 
SELECT p.Name, p.Gender 
FROM Persons as p 
WHERE p.Name in ('Eve', 'Mary')

inline view

SELECT p.Name, p.Gender 
FROM Persons as p 
join (select p2.Gender from Persons as p2 where p2.Name = 'Lucy') as p3 on p.Gender = p3.Gender

dictionary query

select * from SCHEMA_TABLES;
select * from SCHEMA_COLUMNS;
select * from SCHEMA_PROPERTIES;

API

The Hiperspace.SQL API can be called from any language that supports DOTNET interop, including Python (using pythonnet). Access via the Hiperspace.SQL.Engine object that is constructed with a reference to any domain space.

Explain

Provides a detailed breakdown of the query execution plan

member engine.Explain (source, parameters : IDictionary<string,obj>) : string array =

Execute

Executes the SQL queries and returns an array of Data Frames

member engine.Execute (source , parameters : IDictionary<string,obj>) : IDictionary<string, obj array> array  =

Parquet

Executes the SQL queries will a n array of filenames (one for each statement) and returns the filenames after writing the results to the Apache Parquet files.

member this.Parquet (source, fileNames, parameters : IDictionary<string,obj>): string array =
Product Compatible and additional computed target framework versions.
.NET net8.0 is compatible.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed.  net9.0 is compatible.  net9.0-android was computed.  net9.0-browser was computed.  net9.0-ios was computed.  net9.0-maccatalyst was computed.  net9.0-macos was computed.  net9.0-tvos was computed.  net9.0-windows was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

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Version Downloads Last updated
2.1.6 92 2/15/2025
2.0.0 46 1/14/2025
1.0.5 106 11/15/2024
1.0.2 96 11/1/2024
1.0.1 144 10/18/2024

# Overview
     This release is primarily concerned with updates to match changes to .NET 9.0 with the release of Visual Studio 17.13 and related libaries.  It also includes an Update to Hiperspace.Rocks to reflect similar changes to RocksDB.

     The implementation of OLAP cube support has also been changed to simplify its use for client applications and allow Fact tables to be used with BI tools that cannot use the binary CubeKey, OLAP Cube Facts now include references to the dimensions.  This allows the removal of BKey (Key represented as an array of bytes) that us *unhelpful* for **Hiperspace.SQL** and **JSON** serialization.

     ## Fact tables
     Fact tables store calculated summaries of the underlying data, but aggregated for real-time access without the need to reevaluate calculations.  Hiperspace Fact tables also support to store of Hierarchy of values - in this example the `sum` of transaction values are stored in the slice "20" for CustomerAccount (sum of all Transactions for an Account) and slice "3" for Customer (sum of all Transactions for a Customer). Both Customer and CustomerAccount elements have navigation reference to CustomerAccount_Fact to retrieve summaries directly.

     Hiperspace OLAP doesn't just store the sum of transactions for fast read, but allows *deltas* to be added without the need for rerun a complete aggregation.  The `@deltaindex` on Transaction allows only the changes within an *epoch* (transactions between the last aggregation and last update) to be selected, and `deltasum` calculates only the difference since the last time the cube was calculated - this enables real-time aggregation to be performed.

     As the `CustomerAccount_Fact` table is versioned, it is possible to view the history of a cube-slice (in a graph) and calculate regression analysis without the need to drill-down to detail rows.