func ExampleSearchResult() {
client, err := elastic.NewClient()
if err != nil {
panic(err)
}
// Do a search
searchResult, err := client.Search().Index("twitter").Query(elastic.NewMatchAllQuery()).Do()
if err != nil {
panic(err)
}
// searchResult is of type SearchResult and returns hits, suggestions,
// and all kinds of other information from Elasticsearch.
fmt.Printf("Query took %d milliseconds\n", searchResult.TookInMillis)
// Each is a utility function that iterates over hits in a search result.
// It makes sure you don't need to check for nil values in the response.
// However, it ignores errors in serialization. If you want full control
// over iterating the hits, see below.
var ttyp Tweet
for _, item := range searchResult.Each(reflect.TypeOf(ttyp)) {
t := item.(Tweet)
fmt.Printf("Tweet by %s: %s\n", t.User, t.Message)
}
fmt.Printf("Found a total of %d tweets\n", searchResult.TotalHits())
// Here's how you iterate hits with full control.
if searchResult.Hits != nil {
fmt.Printf("Found a total of %d tweets\n", searchResult.Hits.TotalHits)
// Iterate through results
for _, hit := range searchResult.Hits.Hits {
// hit.Index contains the name of the index
// Deserialize hit.Source into a Tweet (could also be just a map[string]interface{}).
var t Tweet
err := json.Unmarshal(*hit.Source, &t)
if err != nil {
// Deserialization failed
}
// Work with tweet
fmt.Printf("Tweet by %s: %s\n", t.User, t.Message)
}
} else {
// No hits
fmt.Print("Found no tweets\n")
}
}
func (es *ElasticSearch) suggester(tsName string, term elastic.Suggester) []elastic.SearchSuggestion {
all := elastic.NewMatchAllQuery()
searchResult, err := es.client.Search().
Index(es.index).
Query(&all).
Suggester(term).
Do()
if err != nil {
log.Fatal(err)
}
result, _ := searchResult.Suggest[tsName]
return result
}
func ExampleAggregations() {
// Get a client to the local Elasticsearch instance.
client, err := elastic.NewClient()
if err != nil {
// Handle error
panic(err)
}
// Create an aggregation for users and a sub-aggregation for a date histogram of tweets (per year).
timeline := elastic.NewTermsAggregation().Field("user").Size(10).OrderByCountDesc()
histogram := elastic.NewDateHistogramAggregation().Field("created").Interval("year")
timeline = timeline.SubAggregation("history", histogram)
// Search with a term query
searchResult, err := client.Search().
Index("twitter"). // search in index "twitter"
Query(elastic.NewMatchAllQuery()). // return all results, but ...
SearchType("count"). // ... do not return hits, just the count
Aggregation("timeline", timeline). // add our aggregation to the query
Pretty(true). // pretty print request and response JSON
Do() // execute
if err != nil {
// Handle error
panic(err)
}
// Access "timeline" aggregate in search result.
agg, found := searchResult.Aggregations.Terms("timeline")
if !found {
log.Fatalf("we sould have a terms aggregation called %q", "timeline")
}
for _, userBucket := range agg.Buckets {
// Every bucket should have the user field as key.
user := userBucket.Key
// The sub-aggregation history should have the number of tweets per year.
histogram, found := userBucket.DateHistogram("history")
if found {
for _, year := range histogram.Buckets {
fmt.Printf("user %q has %d tweets in %q\n", user, year.DocCount, year.KeyAsString)
}
}
}
}