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Add Search() function, README and fix some lint errors This commit changes the internal `search()` function into an exposed `Search()` function that can be used to execute queries against an instance of an ElasticSearch client. The per-query-type methods of `Run()` are removed for now to prevent having to create them for every type. `Search()` is agnostic. A README.md file is added with some information, and a few lingering lint errors are fixed.
2020-02-18 16:43:19 +00:00
# esquery
Refactor API, add aggregations and custom queries This commit introduces a refactor of the codebase and the API, to make it more user friendly. Queries can now directly be executed via the `Run()` method. Internally, the library no longer uses JSON generation as a major mechanism, instead all types need to implement a `Mappable` interface which simply turns each type in a `map[string]interface{}`, which is what the ElasticSearch client expects. This makes the code easier to write, and makes writing tests less error prone, as JSON need not be written directly. Support for metrics aggregations is also added. However, aggregations of type bucket, pipeline and matrix are not supported yet. To make the library more useful in its current state, support is added for running custom queries and aggregations, via the `CustomQuery()` and `CustomAgg()` functions, which both accepts an arbitrary `map[string]interface{}`.
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**esquery** is a non-obtrusive, idiomatic and easy-to-use query and aggregation builder for the [official Go client](https://github.com/elastic/go-elasticsearch) for [ElasticSearch](https://www.elastic.co/products/elasticsearch). It alleviates the need to use extremely nested maps (`map[string]interface{}`) and serializing queries to JSON manually. It also helps eliminating common mistakes such as misspelling query types, as everything is statically typed.
Save yourself some joint aches and many lines of code by switching for maps to `esquery`. Wanna know how much code you'll save? just read this project's test.
Add Search() function, README and fix some lint errors This commit changes the internal `search()` function into an exposed `Search()` function that can be used to execute queries against an instance of an ElasticSearch client. The per-query-type methods of `Run()` are removed for now to prevent having to create them for every type. `Search()` is agnostic. A README.md file is added with some information, and a few lingering lint errors are fixed.
2020-02-18 16:43:19 +00:00
## Usage
Refactor API, add aggregations and custom queries This commit introduces a refactor of the codebase and the API, to make it more user friendly. Queries can now directly be executed via the `Run()` method. Internally, the library no longer uses JSON generation as a major mechanism, instead all types need to implement a `Mappable` interface which simply turns each type in a `map[string]interface{}`, which is what the ElasticSearch client expects. This makes the code easier to write, and makes writing tests less error prone, as JSON need not be written directly. Support for metrics aggregations is also added. However, aggregations of type bucket, pipeline and matrix are not supported yet. To make the library more useful in its current state, support is added for running custom queries and aggregations, via the `CustomQuery()` and `CustomAgg()` functions, which both accepts an arbitrary `map[string]interface{}`.
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esquery provides a [method chaining](https://en.wikipedia.org/wiki/Method_chaining)-style API for building and executing queries and aggregations. It does not wrap the official Go client nor does it require you to change your existing code in order to integrate the library. Queries can be directly built with `esquery`, and executed by passing an `*elasticsearch.Client` instance (with optional search parameters). Results are returned as-is from the official client (e.g. `*esapi.Response` objects).
Getting started is extremely simple:
Add Search() function, README and fix some lint errors This commit changes the internal `search()` function into an exposed `Search()` function that can be used to execute queries against an instance of an ElasticSearch client. The per-query-type methods of `Run()` are removed for now to prevent having to create them for every type. `Search()` is agnostic. A README.md file is added with some information, and a few lingering lint errors are fixed.
2020-02-18 16:43:19 +00:00
```go
package main
import (
"context"
"log"
"bitbucket.org/scalock/esquery"
"github.com/elastic/go-elasticsearch/v7"
)
func main() {
Refactor API, add aggregations and custom queries This commit introduces a refactor of the codebase and the API, to make it more user friendly. Queries can now directly be executed via the `Run()` method. Internally, the library no longer uses JSON generation as a major mechanism, instead all types need to implement a `Mappable` interface which simply turns each type in a `map[string]interface{}`, which is what the ElasticSearch client expects. This makes the code easier to write, and makes writing tests less error prone, as JSON need not be written directly. Support for metrics aggregations is also added. However, aggregations of type bucket, pipeline and matrix are not supported yet. To make the library more useful in its current state, support is added for running custom queries and aggregations, via the `CustomQuery()` and `CustomAgg()` functions, which both accepts an arbitrary `map[string]interface{}`.
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// connect to an ElasticSearch instance
Add Search() function, README and fix some lint errors This commit changes the internal `search()` function into an exposed `Search()` function that can be used to execute queries against an instance of an ElasticSearch client. The per-query-type methods of `Run()` are removed for now to prevent having to create them for every type. `Search()` is agnostic. A README.md file is added with some information, and a few lingering lint errors are fixed.
2020-02-18 16:43:19 +00:00
es, err := elasticsearch.NewDefaultClient()
if err != nil {
log.Fatalf("Failed creating client: %s", err)
}
Refactor API, add aggregations and custom queries This commit introduces a refactor of the codebase and the API, to make it more user friendly. Queries can now directly be executed via the `Run()` method. Internally, the library no longer uses JSON generation as a major mechanism, instead all types need to implement a `Mappable` interface which simply turns each type in a `map[string]interface{}`, which is what the ElasticSearch client expects. This makes the code easier to write, and makes writing tests less error prone, as JSON need not be written directly. Support for metrics aggregations is also added. However, aggregations of type bucket, pipeline and matrix are not supported yet. To make the library more useful in its current state, support is added for running custom queries and aggregations, via the `CustomQuery()` and `CustomAgg()` functions, which both accepts an arbitrary `map[string]interface{}`.
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// run a boolean search query
qRes, err := esquery.Query(
Add Search() function, README and fix some lint errors This commit changes the internal `search()` function into an exposed `Search()` function that can be used to execute queries against an instance of an ElasticSearch client. The per-query-type methods of `Run()` are removed for now to prevent having to create them for every type. `Search()` is agnostic. A README.md file is added with some information, and a few lingering lint errors are fixed.
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esquery.
Bool().
Must(esquery.Term("title", "Go and Stuff")).
Filter(esquery.Term("tag", "tech")),
Refactor API, add aggregations and custom queries This commit introduces a refactor of the codebase and the API, to make it more user friendly. Queries can now directly be executed via the `Run()` method. Internally, the library no longer uses JSON generation as a major mechanism, instead all types need to implement a `Mappable` interface which simply turns each type in a `map[string]interface{}`, which is what the ElasticSearch client expects. This makes the code easier to write, and makes writing tests less error prone, as JSON need not be written directly. Support for metrics aggregations is also added. However, aggregations of type bucket, pipeline and matrix are not supported yet. To make the library more useful in its current state, support is added for running custom queries and aggregations, via the `CustomQuery()` and `CustomAgg()` functions, which both accepts an arbitrary `map[string]interface{}`.
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).Run(
es,
es.Search.WithContext(context.TODO()),
es.Search.WithIndex("test"),
)
if err != nil {
log.Fatalf("Failed searching for stuff: %s", err)
}
defer qRes.Body.Close()
// run an aggregation
aRes, err := esquery.Aggregate(
esquery.Avg("average_score", "score"),
esquery.Max("max_score", "score"),
).Run(
es,
Add Search() function, README and fix some lint errors This commit changes the internal `search()` function into an exposed `Search()` function that can be used to execute queries against an instance of an ElasticSearch client. The per-query-type methods of `Run()` are removed for now to prevent having to create them for every type. `Search()` is agnostic. A README.md file is added with some information, and a few lingering lint errors are fixed.
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es.Search.WithContext(context.TODO()),
es.Search.WithIndex("test"),
)
if err != nil {
log.Fatalf("Failed searching for stuff: %s", err)
}
Refactor API, add aggregations and custom queries This commit introduces a refactor of the codebase and the API, to make it more user friendly. Queries can now directly be executed via the `Run()` method. Internally, the library no longer uses JSON generation as a major mechanism, instead all types need to implement a `Mappable` interface which simply turns each type in a `map[string]interface{}`, which is what the ElasticSearch client expects. This makes the code easier to write, and makes writing tests less error prone, as JSON need not be written directly. Support for metrics aggregations is also added. However, aggregations of type bucket, pipeline and matrix are not supported yet. To make the library more useful in its current state, support is added for running custom queries and aggregations, via the `CustomQuery()` and `CustomAgg()` functions, which both accepts an arbitrary `map[string]interface{}`.
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defer aRes.Body.Close()
Add Search() function, README and fix some lint errors This commit changes the internal `search()` function into an exposed `Search()` function that can be used to execute queries against an instance of an ElasticSearch client. The per-query-type methods of `Run()` are removed for now to prevent having to create them for every type. `Search()` is agnostic. A README.md file is added with some information, and a few lingering lint errors are fixed.
2020-02-18 16:43:19 +00:00
Refactor API, add aggregations and custom queries This commit introduces a refactor of the codebase and the API, to make it more user friendly. Queries can now directly be executed via the `Run()` method. Internally, the library no longer uses JSON generation as a major mechanism, instead all types need to implement a `Mappable` interface which simply turns each type in a `map[string]interface{}`, which is what the ElasticSearch client expects. This makes the code easier to write, and makes writing tests less error prone, as JSON need not be written directly. Support for metrics aggregations is also added. However, aggregations of type bucket, pipeline and matrix are not supported yet. To make the library more useful in its current state, support is added for running custom queries and aggregations, via the `CustomQuery()` and `CustomAgg()` functions, which both accepts an arbitrary `map[string]interface{}`.
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// ...
Add Search() function, README and fix some lint errors This commit changes the internal `search()` function into an exposed `Search()` function that can be used to execute queries against an instance of an ElasticSearch client. The per-query-type methods of `Run()` are removed for now to prevent having to create them for every type. `Search()` is agnostic. A README.md file is added with some information, and a few lingering lint errors are fixed.
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}
```
## Notes
Refactor API, add aggregations and custom queries This commit introduces a refactor of the codebase and the API, to make it more user friendly. Queries can now directly be executed via the `Run()` method. Internally, the library no longer uses JSON generation as a major mechanism, instead all types need to implement a `Mappable` interface which simply turns each type in a `map[string]interface{}`, which is what the ElasticSearch client expects. This makes the code easier to write, and makes writing tests less error prone, as JSON need not be written directly. Support for metrics aggregations is also added. However, aggregations of type bucket, pipeline and matrix are not supported yet. To make the library more useful in its current state, support is added for running custom queries and aggregations, via the `CustomQuery()` and `CustomAgg()` functions, which both accepts an arbitrary `map[string]interface{}`.
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* `esquery` currently supports version 7 of the ElasticSearch Go client.
Add Search() function, README and fix some lint errors This commit changes the internal `search()` function into an exposed `Search()` function that can be used to execute queries against an instance of an ElasticSearch client. The per-query-type methods of `Run()` are removed for now to prevent having to create them for every type. `Search()` is agnostic. A README.md file is added with some information, and a few lingering lint errors are fixed.
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* The library cannot currently generate "short queries". For example, whereas
ElasticSearch can accept this:
```json
{ "query": { "term": { "user": "Kimchy" } } }
```
The library will always generate this:
```json
{ "query": { "term": { "user": { "value": "Kimchy" } } } }
```
This is also true for queries such as "bool", where fields like "must" can
either receive one query object, or an array of query objects. `esquery` will
generate an array even if there's only one query object.
Refactor API, add aggregations and custom queries This commit introduces a refactor of the codebase and the API, to make it more user friendly. Queries can now directly be executed via the `Run()` method. Internally, the library no longer uses JSON generation as a major mechanism, instead all types need to implement a `Mappable` interface which simply turns each type in a `map[string]interface{}`, which is what the ElasticSearch client expects. This makes the code easier to write, and makes writing tests less error prone, as JSON need not be written directly. Support for metrics aggregations is also added. However, aggregations of type bucket, pipeline and matrix are not supported yet. To make the library more useful in its current state, support is added for running custom queries and aggregations, via the `CustomQuery()` and `CustomAgg()` functions, which both accepts an arbitrary `map[string]interface{}`.
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## Supported Queries
Add Search() function, README and fix some lint errors This commit changes the internal `search()` function into an exposed `Search()` function that can be used to execute queries against an instance of an ElasticSearch client. The per-query-type methods of `Run()` are removed for now to prevent having to create them for every type. `Search()` is agnostic. A README.md file is added with some information, and a few lingering lint errors are fixed.
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The following queries are currently supported:
Refactor API, add aggregations and custom queries This commit introduces a refactor of the codebase and the API, to make it more user friendly. Queries can now directly be executed via the `Run()` method. Internally, the library no longer uses JSON generation as a major mechanism, instead all types need to implement a `Mappable` interface which simply turns each type in a `map[string]interface{}`, which is what the ElasticSearch client expects. This makes the code easier to write, and makes writing tests less error prone, as JSON need not be written directly. Support for metrics aggregations is also added. However, aggregations of type bucket, pipeline and matrix are not supported yet. To make the library more useful in its current state, support is added for running custom queries and aggregations, via the `CustomQuery()` and `CustomAgg()` functions, which both accepts an arbitrary `map[string]interface{}`.
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| ElasticSearch DSL | `esquery` Function |
Add Search() function, README and fix some lint errors This commit changes the internal `search()` function into an exposed `Search()` function that can be used to execute queries against an instance of an ElasticSearch client. The per-query-type methods of `Run()` are removed for now to prevent having to create them for every type. `Search()` is agnostic. A README.md file is added with some information, and a few lingering lint errors are fixed.
2020-02-18 16:43:19 +00:00
| ------------------------|---------------------- |
| `"match"` | `Match()` |
| `"match_bool_prefix"` | `MatchBoolPrefix()` |
| `"match_phrase"` | `MatchPhrase()` |
| `"match_phrase_prefix"` | `MatchPhrasePrefix()` |
| `"match_all"` | `MatchAll()` |
| `"match_none"` | `MatchNone()` |
| `"exists"` | `Exists()` |
| `"fuzzy"` | `Fuzzy()` |
| `"ids"` | `IDs()` |
| `"prefix"` | `Prefix()` |
| `"range"` | `Range()` |
| `"regexp"` | `Regexp()` |
| `"term"` | `Term()` |
| `"terms"` | `Terms()` |
| `"terms_set"` | `TermsSet()` |
| `"wildcard"` | `Wildcard()` |
| `"bool"` | `Bool()` |
| `"boosting"` | `Boosting()` |
| `"constant_score"` | `ConstantScore()` |
| `"dis_max"` | `DisMax()` |
Refactor API, add aggregations and custom queries This commit introduces a refactor of the codebase and the API, to make it more user friendly. Queries can now directly be executed via the `Run()` method. Internally, the library no longer uses JSON generation as a major mechanism, instead all types need to implement a `Mappable` interface which simply turns each type in a `map[string]interface{}`, which is what the ElasticSearch client expects. This makes the code easier to write, and makes writing tests less error prone, as JSON need not be written directly. Support for metrics aggregations is also added. However, aggregations of type bucket, pipeline and matrix are not supported yet. To make the library more useful in its current state, support is added for running custom queries and aggregations, via the `CustomQuery()` and `CustomAgg()` functions, which both accepts an arbitrary `map[string]interface{}`.
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### Custom Queries
To execute an arbitrary query, or any query that is not natively supported by the library yet, use the `CustomQuery()` function, which accepts any `map[string]interface{}` value.
## Supported Aggregations
The following aggregations are currently supported:
| ElasticSearch DSL | `esquery` Function |
| ------------------------|---------------------- |
| `"avg"` | `Avg()` |
| `"weighted_avg"` | `WeightedAvg()` |
| `"cardinality"` | `Cardinality()` |
| `"max"` | `Max()` |
| `"min"` | `Min()` |
| `"sum"` | `Sum()` |
| `"value_count"` | `ValueCount()` |
| `"percentiles"` | `Percentiles()` |
| `"stats"` | `Stats()` |
| `"string_stats"` | `StringStats()` |
### Custom Aggregations
To execute an arbitrary aggregation, or any aggregation that is not natively supported by the library yet, use the `CustomAgg()` function, which accepts any `map[string]interface{}` value.