Druid4Net 2.2.0

.NET Standard 1.6 .NET Framework 4.5
NuGet\Install-Package Druid4Net -Version 2.2.0
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.
dotnet add package Druid4Net --version 2.2.0
<PackageReference Include="Druid4Net" Version="2.2.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Druid4Net --version 2.2.0
#r "nuget: Druid4Net, 2.2.0"
#r directive can be used in F# Interactive, C# scripting and .NET Interactive. Copy this into the interactive tool or source code of the script to reference the package.
// Install Druid4Net as a Cake Addin
#addin nuget:?package=Druid4Net&version=2.2.0

// Install Druid4Net as a Cake Tool
#tool nuget:?package=Druid4Net&version=2.2.0

druid4net

A .NET Apache Druid client written in C#

Supports .NET 4.5 and above, .NET Standard 1.6 and 2.0

Getting started

  1. Add a reference to druid4net from Nuget or download and reference the dll from releases
  2. Add your favorite JSON parser (if you don't already have one referenced)
  3. Implement the IJsonSerializer interface
  4. Create a DruidClient and start querying

Querying

To query druid, create an instance of the DruidClient using code similar to the following:

var options = new ConfigurationOptions()
{
  JsonSerializer = new JilSerializer(),
  QueryApiBaseAddress = new Uri("http://localhost:8082")
};
new DruidClient(options);

Note the JilSerializer implementation can be found in the Integration tests project along with sample queries of all supported query types.

Timeseries

See Apache Druid Timeseries query documentation for more details on this type of query.

The following example query is performing a timeseries query against the sample wikiticker datasource. It filters the data where the country code is 'US' and the data timestamp is within the specified date interval. It then returns the total pages added by hour in a descending order.

var response = _druidClient.Timeseries<T>(q => q
  .Descending(true)
  .Aggregations(new LongSumAggregator("totalAdded", "added"))
  .Filter(new SelectorFilter("countryIsoCode", "US"))
  .DataSource("wikiticker")
  .Interval(FromDate, ToDate)
  .Granularity(Granularities.Hour)
);

TopN

See Apache Druid TopN query documentation for more details on this type of query.

The following example query is performing a topN query against the sample wikiticker datasource. It filters the data where the country code is 'US' and the user was anonymous and the data timestamp is within the specified date interval. It then returns the top 5 pages by count.

var response = _druidClient.TopN<T>(q => q
  .Metric("totalCount")
  .Dimension("page")
  .Threshold(5)
  .Aggregations(new LongSumAggregator("totalCount", "count"))
  .Filter(new AndFilter(
    new SelectorFilter("isAnonymous", "true"),
    new SelectorFilter("countryIsoCode", "US")
  ))
  .DataSource("wikiticker")
  .Interval(FromDate, ToDate)
  .Granularity(Granularities.All)
);

GroupBy

See Apache Druid GroupBy query documentation for more details on this type of query.

The following example query is performing a groupBy query against the sample wikiticker datasource. It returns the sum of page count grouped by Country name, then by city name and finally by page name.

var response = _druidClient.GroupBy<T>(q => q
  .Dimensions("countryName", "cityName", "page")
  .Aggregations(new LongSumAggregator("totalCount", "count"))
  .DataSource("wikiticker")
  .Interval(FromDate, ToDate)
  .Granularity(Granularities.All)
);

Select

See Apache Druid Select query documentation for more details on this type of query.

The following example query is performing a select query against the sample wikiticker datasource. It selects the country name, city name, page, added and deleted values, filtered to anonymous users and limited to 10 records.

var response = _druidClient.Select<T>(q => q
  .Dimensions("countryName", "cityName", "page")
  .Metrics("added", "deleted")
  .Paging(new PagingSpec(10))
  .Filter(new SelectorFilter("isAnonymous", "true"))
  .DataSource("wikiticker")
  .Interval(FromDate, ToDate)
);

See Apache Druid Search query documentation for more details on this type of query.

The following example query is performing a search query against the sample wikiticker datasource. It searches for pages that contain the term "Dragon" and returns the page dimension value limited to the top 10 records.

var response = _druidClient.Search(q => q
  .DataSource("wikiticker")
  .Granularity(Granularities.All)
  .SearchDimensions("page")
  .Query(new ContainsSearchQuery("Dragon"))
  .Limit(10)
  .Interval(FromDate, ToDate)
);

TimeBoundary

See Apache Druid TimeBoundary query documentation for more details on this type of query.

The following example query is performing a timeBoundary query against the sample wikiticker datasource. It finds the minimum and maximum data points filtered to anonymous users.

var response = _druidClient.TimeBoundary(q => q
  .DataSource("wikiticker")
  .Filter(new SelectorFilter("isAnonymous", "true"))
);

Scan

See Apache Druid TimeBoundary query documentation for more details on this type of query.

The following example query is performing a scan query against the sample wikiticker datasource. It returns druid records in streaming mode, filtered to anonymous users and limited to the first 10 results.

var response = _druidClient.Scan<T>(q => q
  .DataSource("wikiticker")
  .Interval(FromDate, ToDate)
  .Filter(new SelectorFilter("isAnonymous", "true"))
  .Limit(10)
);

Async queries

All query types have both synchronous and asynchronous methods available.

For example:

var response = _druidClient.Timeseries<T>(q => q...);

var response = await _druidClient.TimeseriesAsync<T>(q => q...);

Notes

Why do I need to implement IJsonSerializer?

The short answer is we wanted no dependencies. We also didn't want to implement our own JSON serialization as there are already so many good libraries out there that do this. Most projects already have a library included in their solution that can be used by implementing the interface in a simple pass-through class.

Not supported yet

  • Union data source
  • Extraction filter
Product Versions
.NET net5.0 net5.0-windows net6.0 net6.0-android net6.0-ios net6.0-maccatalyst net6.0-macos net6.0-tvos net6.0-windows
.NET Core netcoreapp1.0 netcoreapp1.1 netcoreapp2.0 netcoreapp2.1 netcoreapp2.2 netcoreapp3.0 netcoreapp3.1
.NET Standard netstandard1.6 netstandard2.0 netstandard2.1
.NET Framework net45 net451 net452 net46 net461 net462 net463 net47 net471 net472 net48
MonoAndroid monoandroid
MonoMac monomac
MonoTouch monotouch
Tizen tizen30 tizen40 tizen60
Xamarin.iOS xamarinios
Xamarin.Mac xamarinmac
Xamarin.TVOS xamarintvos
Xamarin.WatchOS xamarinwatchos
Compatible target framework(s)
Additional computed target framework(s)
Learn more about Target Frameworks and .NET Standard.
  • .NETFramework 4.5

    • No dependencies.
  • .NETStandard 1.6

  • .NETStandard 2.0

    • No dependencies.

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last updated
2.2.0 49,744 7/5/2021
2.1.1 3,245 3/18/2021
2.0.4 492 1/19/2021
2.0.3 343 11/19/2020
2.0.2 11,110 8/12/2019
2.0.1 967 3/29/2019
2.0.0 689 1/3/2019