Spark 整合ElasticSearch
因為做資料搜索用到了ElasticSearch,最近又了解一下 Spark ML,先來演示一個Spark 讀取/寫入 ElasticSearch 簡單示例。(spark 讀取ElasticSearch中數據)
環境:IDEA2016,JDK8,windows10,安裝的 ElasticSearch6.3.2 和 spark-2.3.1-bin-hadoop2.7,使用mvn package 將程序打成jar包,采用spark-submit提交給spark執行。
先在ElasticSearch中創建一個索引用來演示。因為是文本數據,因此采用ik分詞。可參考:elasticsearch-ik
-
創建索引:PUT /index_ik_test
-
設置mapping 及相應的分詞器,這里指定 content 字段為 ElasticSearch 的text 類型,並使用ik_max_word 分詞模式
POST index_ik_test/fulltext/_mapping
{
"properties": {
"content":{
"type": "text",
"analyzer": "ik_max_word",
"search_analyzer": "ik_max_word"
}
}
} -
存幾篇文檔到ElasticSearch中
POST index_ik_test/fulltext/1
{"content":"其中有兩個人受傷了"} -
ik 分詞器有兩種分詞模式:
ik_max_word
和ik_smart
。可通過如下方式查看一下這兩者的區別:GET index_ik_test/_analyze
{
"text": ["其中國家投資了500萬"],
"tokenizer": "ik_smart"
}分詞結果:其中、國家、投資、了、500萬
GET index_ik_test/_analyze
{
"text": ["其中國家投資了500萬"],
"tokenizer": "ik_max_word"
}分詞結果:其中、中國、國家、投資、了、500、萬
-
使用
GET index_ik_test/_mapping
可查看索引的配置信息{
"index_ik_test": {
"mappings": {
"fulltext": {
"properties": {
"content": {
"type": "text",
"analyzer": "ik_max_word"
}
}
}
}
}
}
好,現在ElasticSearch中有數據了,現在看怎么基於Spark讀取ElasticSearch中的數據。
IDEA2016中新建一個Maven工程,當然也可以用SpringBoot工程,但是這里的是單純的Maven Project。
ElasticSearch官方提供了elasticsearch-hadoop
來供Spark訪問ElasticSearch。具體可參考:官方文檔es for spark。
官方提供了elasticsearch-hadoop
maven 依賴,這個依賴包括了:ElasticSearch for Hadoop MR、ElasticSearch for Hadoop Hive、ElasticSearch for Hadoop Spark。如果只用到了Spark,也可以只添加ElasticSearch for spark依賴。具體可參考:(這個鏈接)[https://www.elastic.co/guide/en/elasticsearch/hadoop/current/install.html]
<dependency>
<groupId>org.elasticsearch</groupId>
<artifactId>elasticsearch-spark-20_2.10</artifactId>
<version>6.3.2</version>
</dependency>
創建spark運行上下文時需要spark-sql_2.11
依賴,可參考:spark 官方文檔quick start。
To build the program, we also write a Maven
pom.xml
file that lists Spark as a dependency. Note that Spark artifacts are tagged with a Scala version.
在本文的示例中,添加了下面3個maven依賴:
<dependency>
<groupId>org.elasticsearch</groupId>
<artifactId>elasticsearch-hadoop</artifactId>
<version>6.3.2</version>
</dependency>
<!-- Spark dependency -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.11</artifactId>
<version>2.3.1</version>
</dependency>
<dependency>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
<version>22.0</version>
</dependency>
下面來直接看示例代碼:
向ElasticSearch中寫入數據
-
spark配置連接ElasticSearch。可參考:elasticsearch-hadoop-master,我們采用的是:Configure the connector to run in WAN mode
SparkConf sparkConf = new SparkConf().setAppName("writeEs").setMaster("local[*]").set("es.index.auto.create", "true") .set("es.nodes", "ELASTIC_SEARCH_IP").set("es.port", "9200").set("es.nodes.wan.only", "true");
-
將數據寫入到ElasticSearch
JavaRDD<Map<String, ?>> javaRDD = jsc.parallelize(ImmutableList.of(numbers, airports)); JavaEsSpark.saveToEs(javaRDD, elasticIndex);
從ElasticSearch查詢數據
JavaRDD<Map<String, Object>> searchRdd = esRDD(jsc, "index_ik_test/fulltext", "?q=中國").values();
for (Map<String, Object> item : searchRdd.collect()) {
item.forEach((key, value)->{
System.out.println("search key:" + key + ", search value:" + value);
});
}
使用?q=中國
作為查詢條件。整個完整示例代碼如下:
import com.google.common.collect.ImmutableList;
import com.google.common.collect.ImmutableMap;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.SparkSession;
import org.elasticsearch.spark.rdd.api.java.JavaEsSpark;
import java.util.Map;
import static org.elasticsearch.spark.rdd.api.java.JavaEsSpark.esRDD;
/**
* Created by Administrator on 2018/8/28.
*/
public class EsSparkTest {
public void writeEs() {
String elasticIndex = "spark/docs";
//https://www.elastic.co/guide/en/elasticsearch/hadoop/current/spark.html#spark-native
SparkConf sparkConf = new SparkConf().setAppName("writeEs").setMaster("local[*]").set("es.index.auto.create", "true")
.set("es.nodes", "ELASTIC_SEARCH_IP").set("es.port", "9200").set("es.nodes.wan.only", "true");
SparkSession sparkSession = SparkSession.builder().config(sparkConf).getOrCreate();
JavaSparkContext jsc = new JavaSparkContext(sparkSession.sparkContext());//adapter
Map<String, ?> numbers = ImmutableMap.of("one", 1, "two", 2);
Map<String, ?> airports = ImmutableMap.of("OTP", "Otopeni", "SFO", "San Fran");
JavaRDD<Map<String, ?>> javaRDD = jsc.parallelize(ImmutableList.of(numbers, airports));
JavaEsSpark.saveToEs(javaRDD, elasticIndex);
}
public void readEs() {
SparkConf sparkConf = new SparkConf().setAppName("writeEs").setMaster("local[*]").set("es.index.auto.create", "true")
.set("es.nodes", "ELASTIC_SEARCH_IP").set("es.port", "9200").set("es.nodes.wan.only", "true");
SparkSession sparkSession = SparkSession.builder().config(sparkConf).getOrCreate();
JavaSparkContext jsc = new JavaSparkContext(sparkSession.sparkContext());//adapter
JavaRDD<Map<String, Object>> searchRdd = esRDD(jsc, "index_ik_test/fulltext", "?q=中國").values();
for (Map<String, Object> item : searchRdd.collect()) {
item.forEach((key, value)->{
System.out.println("search key:" + key + ", search value:" + value);
});
}
sparkSession.stop();
}
}
DemoApplication.java 入口main類
public class DemoApplication {
public static void main(String[] args) {
new EsSparkTest().readEs();
}
}
IDEA菜單欄:view ---> window tools --->maven projects 打開maven 側邊欄。直接雙擊package打包。
$rz -bey esdemo-1.0-SNAPSHOT.jar 將打成的jar包上傳到部署spark服務器上,使用如下命令提交運行:
~/spark-2.3.1-bin-hadoop2.7/bin/spark-submit --class DemoApplication esdemo-1.0-SNAPSHOT.jar
--class 是類的全路徑名。如果執行過程中拋出ClassNotFoundException異常,要看一下pom.xml中指定的依賴是否在Spark安裝目錄下的 jars/ 目錄下(比如事先把Guava jar 和 elasticsearch-hadoop-6.3.2.jar 上傳到 jars/目錄下)。最終執行readEs()方法查詢得到的文檔如下:
因為 content 字段采用的是ik_max_word
分詞模式,因此文本其中國家投資了500萬
分詞結果中包含了 中國
,從而使得這篇document被查詢到了。
后期補充:
在使用Spark 查詢ElasticSearch中數據時,由於ElasticSearch索引user
中定義了一個日期字段,如下:
"created": {
"type": "date",
"format": "yyyy-MM-dd HH:mm:ss"
}
導致Spark執行下面語句查詢
JavaRDD<Map<String, Object>> searchRdd = JavaEsSpark.esRDD(jsc, "user/profile", "?q=test").values();
for (Map<String, Object> item : searchRdd.collect()) {
item.forEach((key, value)->{
System.out.println("search key:" + key + ", search value:" + value);
});
}
反序列化構建日期對象時,報錯:
Caused by: org.elasticsearch.hadoop.EsHadoopIllegalArgumentException: Cannot invoke method public org.joda.time.DateTime org.joda.time.format.DateTimeFormatter.parseDateTime(java.lang.String)
at org.elasticsearch.hadoop.util.ReflectionUtils.invoke(ReflectionUtils.java:93)
at org.elasticsearch.hadoop.util.DateUtils$JodaTime.parseDate(DateUtils.java:105)
at org.elasticsearch.hadoop.util.DateUtils.parseDate(DateUtils.java:122)
at org.elasticsearch.hadoop.serialization.builder.JdkValueReader.parseDate(JdkValueReader.java:424)
at org.elasticsearch.hadoop.serialization.builder.JdkValueReader.date(JdkValueReader.java:412)
at org.elasticsearch.hadoop.serialization.builder.JdkValueReader.readValue(JdkValueReader.java:88)
at org.elasticsearch.hadoop.serialization.ScrollReader.parseValue(ScrollReader.java:789)
at org.elasticsearch.hadoop.serialization.ScrollReader.read(ScrollReader.java:739)
... 31 more
Caused by: java.lang.reflect.InvocationTargetException
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.elasticsearch.hadoop.util.ReflectionUtils.invoke(ReflectionUtils.java:91)
... 38 more
Caused by: java.lang.IllegalArgumentException: Invalid format: "2018-10-08 19:00:41" is malformed at " 19:00:41"
at org.joda.time.format.DateTimeFormatter.parseDateTime(DateTimeFormatter.java:945)
... 43 more
這應該是我索引中定義的日期格式是yyyy-MM-dd HH:mm:ss
,而org.joda.time.format.DateTimeFormatter
默認使用的日期格式不同導致的,但是又不知道在哪里指定日期格式進行Format,所以真的是又遇到了個坑……
如下測試,joda 是支持如下格式的日期格式的:
String pattern = "yyyy-MM-dd HH:mm:ss";
String aTime = "2018-10-08 19:00:41";
DateTimeFormatter format = DateTimeFormat.forPattern(pattern);
DateTime dateTime = format.parseDateTime(aTime);//no error
spark2.3中依賴的:joda的版本如下:
~/spark-2.3.1-bin-hadoop2.7/jars$ ls | grep joda
joda-time-2.9.3.jar