Wabisabi is a Scala Elasticsearch client that uses the REST API and has no dependency on Elasticsearch itself. It is extremely minimal, eschewing any sort of parsing, formatting or other such complication. You can read about why I wrote it if you like.
Wabisabi is based on the dispatch
asynchronous HTTP library. Therefore, all of the returned values are
Future[Response].
The returned object is a Response
from the async-http-client library. Normally you'll want to use getResponseBody
to get the response but you can also check getStatusCode to verify something
didn't go awry. Since the returned response object is wrapped in a Future, you would need to map over it to get a
Future of response code or body, e.g.:
val futureStatusCode: Future[Int] = client.verifyIndex("foo").map(_.getStatusCode)Or,
val futureResponseBody: Future[String] = client.verifyIndex("foo").map(_.getResponseBody)Depends on dispatch and grizzled-slf4j. It's compiled for scala 2.11 and 2.12.
This does not implement every piece of the Elasticsearch API. I will add other bits as needed or as patches arrive.
// Add the Dep
libraryDependencies += "com.github.gphat" %% "wabisabi" % "2.2.0"See the API docs here!
import scala.concurrent.Await
import scala.concurrent.duration._
import wabisabi._
val client = new Client("http://localhost:9200")
// Get the cluster's health
client.health
// Create the index
client.createIndex(name = "foo")
// Verify the index exists
client.verifyIndex("foo").map(_.getStatusCode) // Should be Future(200)
// Get mapping
client.getMapping(indices = Seq("foo"), types = Seq("bar"))
// Put mapping
client.putMapping(indices = Seq("foo"), `type` = "bar",
body = "{\"bar\": {\"properties\": {\"baz\": {\"type\": \"string\"}}}}"
)
// Add a document to the index.
client.index(
index = "foo", `type` = "foo", id = Some("foo"),
data = "{\"foo\":\"bar\"}", refresh = true
)
// Fetch that document by it's id.
client.get("foo", "foo", "foo").map(_.getResponseBody)
// Search for all documents.
client.search(index = "foo", query = "{\"query\": {\"match_all\": {}}}").map(_.getResponseBody)
// Search for all documents of a specific type!
client.search(index = "foo", query = "{\"query\": {\"match_all\": {}}}", `type`= "tweet").map(_.getResponseBody)
// SearchUriParameters case class allows for customised search URI parameters, such as search_type to be passed in a search request as per [this](http://www.elastic.co/guide/en/elasticsearch/reference/current/search-uri-request.html) reference document.
// The list of different search types, in addition to documentation on how each search type is executed by elasticsearch can be seen [here](http://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-search-type.html).
// For example, to search for all documents with `Count` search type:
client.search(index = "foo", query = "{\"query\": {\"match_all\": {}}}",
uriParameters = SearchUriParameters(searchType = Some(Count)))
// To retrieve large numbers of documents (e.g. all the available documents) from elasticsearch efficiently without sorting,
// issue a search request with `Scan` search type, followed by some scroll requests, as per [this](https://www.elastic.co/guide/en/elasticsearch/guide/master/scan-scroll.html) reference document.
// A scroll timeout needs to be passed in both the initial search request and the following scroll requests:
val searchResponse = client.search(index = "foo", query = "{\"query\": {\"match_all\": {}}}",
uriParameters = SearchUriParameters(scroll = Some("1m"), searchType = Some(Scan)))
val searchScrollId = // Extract _scroll_id from the search response body using your favourite JSON decoder library.
val firstScrollResponse = client.scroll("1m", searchScrollId)
val firstPageOfResults = // Extract results from the first scroll response.
val nextScrollId = // Extract _scroll_id from the first scroll response.
// Continue with subsequent scroll requests using the _scroll_id returned from previous requests until no more hits are returned.
// Fetch all the documents by ids.
// MGetUriParameters case class allows you to specify the source fields in result documents.
val mgetResponse = client.mget(index = "foo",`type` = Some("tweet"), query = "{\"ids\":[\"1\", \"2\"]}",
uriParameters = MGetUriParameters(sourceFields = Seq("name", "age")))
// Validate a query.
client.validate(index = "foo", query = "{\"query\": {\"match_all\": {}}}").map(_.getStatusCode) // Should be Future(200)
// Explain a query.
client.explain(index = "foo", `type` = "foo", id = "foo2", query = "{\"query\": {\"term\": {\"foo\":\"bar\"}}}")
// Suggestion possible term/phrase completions.
client.suggest(index = "foo", query = "{\"suggest\": {\"text\": \"bar\", \"completion\": {\"field\": \"foo\"}}}")
// Delete the document.
client.delete("foo", "foo", "foo")
// Delete by query, if you prefer
client.deleteByQuery(Seq("foo"), Seq.empty[String], "{\"match_all\": {}}")
// Count the matches to a query
client.count(Seq("foo"), Seq("foo"), "{\"query\": {\"match_all\": {}}}").map(_.getResponseBody)
// Delete the index
client.deleteIndex("foo")
// Shut down the client. NOTE: This will also shutdown any other Dispatch-based
// HTTP stuff you have going on. Be careful!
Client.shutdown()