1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
|
/*
* Licensed to Elasticsearch under one or more contributor
* license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright
* ownership. Elasticsearch licenses this file to you under
* the Apache License, Version 2.0 (the "License"); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
package org.elasticsearch.index.suggest.stats;
import org.elasticsearch.action.admin.cluster.node.stats.NodeStats;
import org.elasticsearch.action.admin.cluster.node.stats.NodesStatsResponse;
import org.elasticsearch.action.admin.indices.stats.IndicesStatsResponse;
import org.elasticsearch.action.suggest.SuggestRequestBuilder;
import org.elasticsearch.action.suggest.SuggestResponse;
import org.elasticsearch.cluster.ClusterState;
import org.elasticsearch.cluster.routing.GroupShardsIterator;
import org.elasticsearch.cluster.routing.ShardIterator;
import org.elasticsearch.cluster.routing.ShardRouting;
import org.elasticsearch.common.settings.Settings;
import org.elasticsearch.search.suggest.phrase.PhraseSuggestionBuilder;
import org.elasticsearch.search.suggest.term.TermSuggestionBuilder;
import org.elasticsearch.test.ESIntegTestCase;
import java.util.HashSet;
import java.util.Set;
import static org.elasticsearch.cluster.metadata.IndexMetaData.SETTING_NUMBER_OF_REPLICAS;
import static org.elasticsearch.cluster.metadata.IndexMetaData.SETTING_NUMBER_OF_SHARDS;
import static org.elasticsearch.test.hamcrest.ElasticsearchAssertions.assertAcked;
import static org.elasticsearch.test.hamcrest.ElasticsearchAssertions.assertAllSuccessful;
import static org.hamcrest.Matchers.equalTo;
import static org.hamcrest.Matchers.greaterThan;
import static org.hamcrest.Matchers.greaterThanOrEqualTo;
import static org.hamcrest.Matchers.lessThanOrEqualTo;
/**
*/
@ESIntegTestCase.ClusterScope(minNumDataNodes = 2)
public class SuggestStatsIT extends ESIntegTestCase {
@Override
protected int numberOfReplicas() {
return 0;
}
public void testSimpleStats() throws Exception {
// clear all stats first
client().admin().indices().prepareStats().clear().execute().actionGet();
final int numNodes = cluster().numDataNodes();
assertThat(numNodes, greaterThanOrEqualTo(2));
final int shardsIdx1 = randomIntBetween(1, 10); // we make sure each node gets at least a single shard...
final int shardsIdx2 = Math.max(numNodes - shardsIdx1, randomIntBetween(1, 10));
final int totalShards = shardsIdx1 + shardsIdx2;
assertThat(numNodes, lessThanOrEqualTo(totalShards));
assertAcked(prepareCreate("test1").setSettings(Settings.builder()
.put(SETTING_NUMBER_OF_SHARDS, shardsIdx1)
.put(SETTING_NUMBER_OF_REPLICAS, 0))
.addMapping("type", "f", "type=string"));
assertAcked(prepareCreate("test2").setSettings(Settings.builder()
.put(SETTING_NUMBER_OF_SHARDS, shardsIdx2)
.put(SETTING_NUMBER_OF_REPLICAS, 0))
.addMapping("type", "f", "type=string"));
assertThat(shardsIdx1 + shardsIdx2, equalTo(numAssignedShards("test1", "test2")));
assertThat(numAssignedShards("test1", "test2"), greaterThanOrEqualTo(2));
ensureGreen();
for (int i = 0; i < randomIntBetween(20, 100); i++) {
index("test" + ((i % 2) + 1), "type", "" + i, "f", "test" + i);
}
refresh();
int suggestAllIdx = scaledRandomIntBetween(20, 50);
int suggestIdx1 = scaledRandomIntBetween(20, 50);
int suggestIdx2 = scaledRandomIntBetween(20, 50);
long startTime = System.currentTimeMillis();
for (int i = 0; i < suggestAllIdx; i++) {
SuggestResponse suggestResponse = addSuggestions(internalCluster().clientNodeClient().prepareSuggest(), i).get();
assertAllSuccessful(suggestResponse);
}
for (int i = 0; i < suggestIdx1; i++) {
SuggestResponse suggestResponse = addSuggestions(internalCluster().clientNodeClient().prepareSuggest("test1"), i).get();
assertAllSuccessful(suggestResponse);
}
for (int i = 0; i < suggestIdx2; i++) {
SuggestResponse suggestResponse = addSuggestions(internalCluster().clientNodeClient().prepareSuggest("test2"), i).get();
assertAllSuccessful(suggestResponse);
}
long endTime = System.currentTimeMillis();
IndicesStatsResponse indicesStats = client().admin().indices().prepareStats().execute().actionGet();
// check current
assertThat(indicesStats.getTotal().getSuggest().getCurrent(), equalTo(0L));
// check suggest count
assertThat(indicesStats.getTotal().getSuggest().getCount(), equalTo((long) (suggestAllIdx * totalShards + suggestIdx1 * shardsIdx1 + suggestIdx2 * shardsIdx2)));
assertThat(indicesStats.getIndices().get("test1").getTotal().getSuggest().getCount(), equalTo((long) ((suggestAllIdx + suggestIdx1) * shardsIdx1)));
assertThat(indicesStats.getIndices().get("test2").getTotal().getSuggest().getCount(), equalTo((long) ((suggestAllIdx + suggestIdx2) * shardsIdx2)));
logger.info("iter {}, iter1 {}, iter2 {}, {}", suggestAllIdx, suggestIdx1, suggestIdx2, endTime - startTime);
// check suggest time
assertThat(indicesStats.getTotal().getSuggest().getTimeInMillis(), greaterThan(0L));
// the upperbound is num shards * total time since we do searches in parallel
assertThat(indicesStats.getTotal().getSuggest().getTimeInMillis(), lessThanOrEqualTo(totalShards * (endTime - startTime)));
NodesStatsResponse nodeStats = client().admin().cluster().prepareNodesStats().execute().actionGet();
NodeStats[] nodes = nodeStats.getNodes();
Set<String> nodeIdsWithIndex = nodeIdsWithIndex("test1", "test2");
int num = 0;
for (NodeStats stat : nodes) {
SuggestStats suggestStats = stat.getIndices().getSuggest();
logger.info("evaluating {}", stat.getNode());
if (nodeIdsWithIndex.contains(stat.getNode().getId())) {
assertThat(suggestStats.getCount(), greaterThan(0L));
assertThat(suggestStats.getTimeInMillis(), greaterThan(0L));
num++;
} else {
assertThat(suggestStats.getCount(), equalTo(0L));
assertThat(suggestStats.getTimeInMillis(), equalTo(0L));
}
}
assertThat(num, greaterThan(0));
}
private SuggestRequestBuilder addSuggestions(SuggestRequestBuilder request, int i) {
for (int s = 0; s < randomIntBetween(2, 10); s++) {
if (randomBoolean()) {
request.addSuggestion(new PhraseSuggestionBuilder("s" + s).field("f").text("test" + i + " test" + (i - 1)));
} else {
request.addSuggestion(new TermSuggestionBuilder("s" + s).field("f").text("test" + i));
}
}
return request;
}
private Set<String> nodeIdsWithIndex(String... indices) {
ClusterState state = client().admin().cluster().prepareState().execute().actionGet().getState();
GroupShardsIterator allAssignedShardsGrouped = state.routingTable().allAssignedShardsGrouped(indices, true);
Set<String> nodes = new HashSet<>();
for (ShardIterator shardIterator : allAssignedShardsGrouped) {
for (ShardRouting routing : shardIterator.asUnordered()) {
if (routing.active()) {
nodes.add(routing.currentNodeId());
}
}
}
return nodes;
}
protected int numAssignedShards(String... indices) {
ClusterState state = client().admin().cluster().prepareState().execute().actionGet().getState();
GroupShardsIterator allAssignedShardsGrouped = state.routingTable().allAssignedShardsGrouped(indices, true);
return allAssignedShardsGrouped.size();
}
}
|
