Flink Hudi 测试

组件版本

将hdfs-site.xml，core-site.xml，hive-site.xml放入resources下

测试代码

1.  
   object TestFlinkSQLOptHudi {
2.  
   private var logger: org.slf4j.Logger = _
3.  
    
4.  
   def main(args: Array[String]): Unit = {
5.  
   logger = LoggerFactory.getLogger(this.getClass.getSimpleName)
6.  
   Logger.getLogger("org.apache").setLevel(Level.WARN)
7.  
   Logger.getLogger("hive.metastore").setLevel(Level.WARN)
8.  
   Logger.getLogger("akka").setLevel(Level.INFO)
9.  
    
10.  
    val tableEnv = FlinkUtils.initStreamTableEnvironment()
11.  
     
12.  
    // datagen source 随机生成数据
13.  
    // val sourceDDL =
14.  
    // """
15.  
    // |create table datagen_source (
16.  
    // | id int,
17.  
    // | data string,
18.  
    // | ts as localtimestamp,
19.  
    // | watermark for ts as ts
20.  
    // |) with (
21.  
    // | 'connector' = 'datagen',
22.  
    // | 'rows-per-second'='10',
23.  
    // | 'fields.id.kind'='sequence',
24.  
    // | 'fields.id.start'='1',
25.  
    // | 'fields.id.end'='100000',
26.  
    // | 'fields.data.length'='5'
27.  
    // |)
28.  
    // |""".stripMargin
29.  
    // tableEnv.executeSql(sourceDDL)
30.  
     
31.  
    // kafka sink
32.  
    // val sinkDDL =
33.  
    // """
34.  
    // |create table kafka_sink (
35.  
    // | id int,
36.  
    // | data string,
37.  
    // | ts timestamp
38.  
    // |) with (
39.  
    // | 'connector' = 'kafka',
40.  
    // | 'topic' = 'kafka_sink',
41.  
    // | 'properties.bootstrap.servers' = 'test-lakehouse:9092',
42.  
    // | 'properties.group.id' = 'lakehouse',
43.  
    // | 'scan.startup.mode' = 'earliest-offset',
44.  
    // | 'format' = 'json',
45.  
    // | 'json.fail-on-missing-field' = 'false',
46.  
    // | 'json.ignore-parse-errors' = 'true'
47.  
    // |)
48.  
    // |""".stripMargin
49.  
    // tableEnv.executeSql(sinkDDL)
50.  
     
51.  
    // insert to kafka
52.  
    // val insertDML =
53.  
    // """
54.  
    // |insert into kafka_sink
55.  
    // |select * from datagen_soure
56.  
    // |""".stripMargin
57.  
    // tableEnv.executeSql(insertDML)
58.  
     
59.  
    // 1. 建表，写表
60.  
    // val writeTableDDL =
61.  
    // """
62.  
    // |create table if not exists hudi_test_table (
63.  
    // | id int,
64.  
    // | data string,
65.  
    // | ts timestamp(3),
66.  
    // | `time` string,
67.  
    // | `date` string
68.  
    // |) partitioned by (`date`)
69.  
    // | with (
70.  
    // | 'connector' = 'hudi',
71.  
    // | 'table.type' = 'MERGE_ON_READ',
72.  
    // | 'path' = 'hdfs://test-lakehouse:9000/lakehouse/hudi_test_table',
73.  
    // // | 'path'='file:///F:\workspace\lakehouse-hudi\test\src\main\resources\hudi_test_table',
74.  
    // | 'write.tasks' = '1',
75.  
    // | 'hoodie.datasource.write.recordkey.field' = 'id',
76.  
    // | 'write.precombine.field' = 'ts',
77.  
    // | 'compaction.tasks' = '1',
78.  
    // | 'compaction.trigger.strategy' = 'num_or_time',
79.  
    // | 'compaction.delta_commits' = '2',
80.  
    // | 'compaction.delta_seconds' = '300'
81.  
    // |)
82.  
    // |""".stripMargin
83.  
    // tableEnv.executeSql(writeTableDDL)
84.  
     
85.  
    // 2. 直接写入数据
86.  
    // val insertDML =
87.  
    // """
88.  
    // |insert into hudi_test_table values
89.  
    // |(1, 'a', timestamp '2021-09-26 00:00:01', '2021-09-26 00:00:01', '2021-09-26'),
90.  
    // |(2, 'b', timestamp '2021-09-26 00:00:02', '2021-09-26 00:00:02', '2021-09-26'),
91.  
    // |(3, 'c', timestamp '2021-09-26 00:00:03', '2021-09-26 00:00:03', '2021-09-26'),
92.  
    // |(4, 'd', timestamp '2021-09-27 00:00:04', '2021-09-27 00:00:04', '2021-09-27'),
93.  
    // |(5, 'e', timestamp '2021-09-27 00:00:05', '2021-09-27 00:00:05', '2021-09-27'),
94.  
    // |(6, 'f', timestamp '2021-09-27 00:00:06', '2021-09-27 00:00:06', '2021-09-27')
95.  
    // |""".stripMargin
96.  
    // tableEnv.executeSql(insertDML)
97.  
    // 查询结果
98.  
    // ---- --- ------- --------------------- --------------------- ------------
99.  
    //| op | d | a | ts | time | date |
100.  
     // ---- --- - -- --------------------- --------------------- ------------
101.  
     //| I | 1 | a | 2021-09-26T00:00:01 | 2021-09-26 00:00:01 | 2021-09-26 |
102.  
     //| I | 2 | b | 2021-09-26T00:00:02 | 2021-09-26 00:00:02 | 2021-09-26 |
103.  
     //| I | 3 | c | 2021-09-26T00:00:03 | 2021-09-26 00:00:03 | 2021-09-26 |
104.  
     //| I | 4 | d | 2021-09-27T00:00:04 | 2021-09-27 00:00:04 | 2021-09-27 |
105.  
     //| I | 5 | e | 2021-09-27T00:00:05 | 2021-09-27 00:00:05 | 2021-09-27 |
106.  
     //| I | 6 | f | 2021-09-27T00:00:06 | 2021-09-27 00:00:06 | 2021-09-27 |
107.  
      
108.  
     // update 数据
109.  
     // val updateDML =
110.  
     // """
111.  
     // |insert into t1 values
112.  
     // |('1','update',timestamp '2021-09-26 12:12:12', date '2021-09-26')
113.  
     // |""".stripMargin
114.  
     // tableEnv.executeSql(updateDML)
115.  
     // 查询结果
116.  
     // ---- --- --------- --------------------- --------------------- ------------
117.  
     //| op | d | a | ts | time | date |
118.  
     // ---- --- -------- --------------------- --------------------- ------------
119.  
     //| I | 1 | update | 2021-09-26T12:12:12 | 2021-09-26 12:12:12 | 2021-09-26 |
120.  
     //| I | 2 | b | 2021-09-26T00:00:02 | 2021-09-26 00:00:02 | 2021-09-26 |
121.  
     //| I | 3 | c | 2021-09-26T00:00:03 | 2021-09-26 00:00:03 | 2021-09-26 |
122.  
     //| I | 4 | d | 2021-09-27T00:00:04 | 2021-09-27 00:00:04 | 2021-09-27 |
123.  
     //| I | 5 | e | 2021-09-27T00:00:05 | 2021-09-27 00:00:05 | 2021-09-27 |
124.  
     //| I | 6 | f | 2021-09-27T00:00:06 | 2021-09-27 00:00:06 | 2021-09-27 |
125.  
      
126.  
     // 3. source 数据写入 hudi
127.  
     // val insertDML =
128.  
     // """
129.  
     // |insert into hudi_test_table
130.  
     // |select
131.  
     // | id,
132.  
     // | data,
133.  
     // | ts,
134.  
     // | date_format(ts, 'yyyy-MM-dd HH:mm:ss') as `time`,
135.  
     // | date_format(ts, 'yyyy-MM-dd') as `date`
136.  
     // |from datagen_source
137.  
     // |""".stripMargin
138.  
     // tableEnv.executeSql(insertDML)
139.  
      
140.  
     // 4. 流表查询
141.  
     tableEnv.executeSql("drop table if exists hudi_test_table")
142.  
     val readTableDDL =
143.  
     """
144.  
     |create table if not exists hudi_test_table (
145.  
     | id int,
146.  
     | data string,
147.  
     | ts timestamp(3),
148.  
     | `time` string,
149.  
     | `date` string
150.  
     |) partitioned by (`date`)
151.  
     | with (
152.  
     | 'connector' = 'hudi',
153.  
     | 'table.type' = 'MERGE_ON_READ',
154.  
     | 'path' = 'hdfs://test-lakehouse:9000/lakehouse/hudi_test_table',
155.  
     | 'hoodie.datasource.write.recordkey.field' = 'id',
156.  
     // | 'hoodie.datasource.query.type' = 'snapshot',
157.  
     | 'read.tasks' = '1',
158.  
     | 'read.streaming.enabled' = 'true',
159.  
     | 'read.streaming.check-interval' = '5',
160.  
     | 'read.streaming.start-commit' = '000',
161.  
     | 'read.utc-timezone' = 'false'
162.  
     |)
163.  
     |""".stripMargin
164.  
     tableEnv.executeSql(readTableDDL)
165.  
      
166.  
     val queryDML =
167.  
     """
168.  
     |select count(distinct id) from hudi_test_table where `date` = '2021-09-30'
169.  
     |""".stripMargin
170.  
     tableEnv.executeSql(queryDML).print()
171.  
      
172.  
     // 或者 print sink
173.  
     val sinkDDL =
174.  
     // val sinkDDL =
175.  
     // """
176.  
     // |create table print_sink (
177.  
     // | id int,
178.  
     // | data string,
179.  
     // | ts timestamp(3),
180.  
     // | `time` string,
181.  
     // | `date` string
182.  
     // |) with (
183.  
     // | 'connector' = 'print'
184.  
     // |)
185.  
     // |""".stripMargin
186.  
     // tableEnv.executeSql(sinkDDL)
187.  
     //
188.  
     // val queryDML =
189.  
     // """
190.  
     // |insert into print_sink
191.  
     // |select * from hudi_test_table
192.  
     // |""".stripMargin
193.  
     // tableEnv.executeSql(queryDML)
194.  
     }
195.  
     }

sql-client 测试

本地测试模式

将 hudi-flink-bundle_2.11-0.9.0.jar 放入 $FLINK_HOME/lib 下，启动sql-client既可。

sql-client embedded

yarn-cluster模式

选择一台服务器创建 session

./bin/yarn-session.sh -d -nm dwd_test -yjm 3g -ytm 10g -ys 2

 检查session是否正常

yarn application -list | grep application_1632050203454_167491

查看 applictionId

在该服务器上每次创建 session，applictionId 都会改变。

1.  
   # cat /tmp/.yarn-properties-user，比如 hdfs用户启动的session
2.  
    
3.  
   cat /tmp/.yarn-properties-hdfs
4.  
    
5.  
   #Generated YARN properties file
6.  
   #Wed Sep 29 17:00:09 CST 2021
7.  
   dynamicPropertiesString=
8.  
   applicationID=application_1632050203454_167491

切换 hdfs 用户启动 sql-client 进行测试，如果 /tmp/.yarn-properties-hdfs 中 applicationId 发生改变，该会话将不可用，所以测试时只创建一次 session，可启动多个 sql-client 多个 Job 往该session提交即可。

1.  
   bin/sql-client.sh embedded -s application_1632050203454_167491
2.  
    
3.  
   # 检查会话是否可用
4.  
   select now();

部分参数设置

1.  
   set execution.checkpointing.interval = 10sec;
2.  
    
3.  
   set execution.result-mode = tableau;
4.  
    
5.  
   set execution.restart-strategy.type = fixed-delay;
6.  
   set execution.restart-strategy.attempts = 10;
7.  
   set execution.restart-strategy.delay = 10000;

建表

1.  
   create table if not exists datagen_source (
2.  
   id int,
3.  
   data string,
4.  
   ts as localtimestamp,
5.  
   watermark for ts as ts
6.  
   ) with (
7.  
   'connector' = 'datagen',
8.  
   --'number-of-rows' = '10000',
9.  
   'rows-per-second'='10',
10.  
    'fields.id.kind'='sequence',
11.  
    'fields.id.start'='1',
12.  
    'fields.id.end'='100000',
13.  
    'fields.data.length'='5'
14.  
    );
15.  
     
16.  
    create table if not exists hudi_test_table(
17.  
    id int,
18.  
    data string,
19.  
    ts timestamp(3),
20.  
    `time` string,
21.  
    `date` string
22.  
    ) comment 'flink hudi ods table : 用户维系记录表'
23.  
    partitioned by (`date`)
24.  
    with (
25.  
    'connector' = 'hudi',
26.  
    'table.type' = 'MERGE_ON_READ',
27.  
    'path' = 'hdfs:///user/hive/datalake/hudi_test_db/hudi_test_table',
28.  
    'read.tasks' = '1',
29.  
    'read.streaming.enabled' = 'true',
30.  
    'read.streaming.check-interval' = '10',
31.  
    'read.streaming.start-commit' = '000',
32.  
    'read.utc-timezone' = 'false',
33.  
    'write.tasks' = '1',
34.  
    'write.rate.limit' = '2000',
35.  
    'write.bucket_assign.tasks' = '3',
36.  
    'write.precombine.field' = 'ts',
37.  
    'write.index_bootstrap.tasks' = '3'
38.  
    'index.global.enabled' = 'true'
39.  
    'index.bootstrap.enabled' = 'true'
40.  
    'index.state.ttl' = '15'
41.  
    'clean.retain_commits' = '60',
42.  
    'hoodie.datasource.write.recordkey.field' = 'id',
43.  
    'hoodie.datasource.write.partitionpath.field' = 'date',
44.  
    'hoodie.datasource.query.type' = 'snapshot',
45.  
    'hoodie.datasource.merge.type' = 'payload_combine',
46.  
    'compaction.tasks' = '1',
47.  
    'compaction.trigger.strategy' = 'num_or_time',
48.  
    'compaction.delta_commits' = '5',
49.  
    'compaction.delta_seconds' = '300',
50.  
    'compaction.max_memory' = '1024'
51.  
    'hive_sync.enable' = 'true',
52.  
    'hive_sync.metastore.uris' = 'thrift://ip:9083',
53.  
    'hive_sync.jdbc_url' = 'jdbc:hive2://ip:10000',
54.  
    'hive_sync.use_jdbc' = 'true',
55.  
    'hive_sync.db' = 'hudi_test_db',
56.  
    'hive_sync.table' = 'hudi_test_table',
57.  
    'hive_sync.partition_fields' = 'date',
58.  
    --'hive_sync.partition_extractor_class' = 'org.apache.hudi.hive.NonPartitionedExtractor',
59.  
    'hive_sync.partition_extractor_class' = 'org.apache.hudi.hive.MultiPartKeysValueExtractor',
60.  
    'hive_sync.file_format' = 'PARQUET',
61.  
    'hive_sync.support_timestamp' = 'true',
62.  
    'hive_sync.username' = 'hive',
63.  
    'hive_sync.password' = '123456'
64.  
    );

写入

1.  
   -- 直接写入
2.  
   insert into hudi_test_table values
3.  
   (1, 'a', timestamp '2021-09-26 00:00:01', '2021-09-26 00:00:01', '2021-09-26'),
4.  
   (2, 'b', timestamp '2021-09-26 00:00:02', '2021-09-26 00:00:02', '2021-09-26'),
5.  
   (3, 'c', timestamp '2021-09-26 00:00:03', '2021-09-26 00:00:03', '2021-09-26'),
6.  
   (4, 'd', timestamp '2021-09-27 00:00:04', '2021-09-27 00:00:04', '2021-09-27'),
7.  
   (5, 'e', timestamp '2021-09-27 00:00:05', '2021-09-27 00:00:05', '2021-09-27'),
8.  
   (6, 'f', timestamp '2021-09-27 00:00:06', '2021-09-27 00:00:06', '2021-09-27');
9.  
    
10.  
    -- 单条 upsert
11.  
    insert into hudi_test_table values
12.  
    (1, 'update', timestamp '2021-09-26 12:12:12', '2021-09-26 12:12:12', '2021-09-26');
13.  
     
14.  
    -- 从 source 写入
15.  
    insert into hudi_test_table
16.  
    select
17.  
    id,
18.  
    data,
19.  
    ts,
20.  
    date_format(ts, 'yyyy-MM-dd HH:mm:ss') as `time`,
21.  
    date_format(ts, 'yyyy-MM-dd') as `date`
22.  
    from datagen_source;

流读

1.  
   set table.dynamic-table-options.enabled = true;
2.  
   select count(0) from
3.  
   /* OPTIONS('read.tasks' = '10', 'read.streaming.enabled' = 'true') */;

pom文件

1.  
   <properties>
2.  
   <!-- project compiler -->
3.  
   <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
4.  
   <maven.compiler.source>1.8</maven.compiler.source>
5.  
   <maven.compiler.target>1.8</maven.compiler.target>
6.  
   <!-- maven compiler-->
7.  
   <scala.maven.plugin.version>3.2.2</scala.maven.plugin.version>
8.  
   <maven.compiler.plugin.version>3.8.1</maven.compiler.plugin.version>
9.  
   <maven.assembly.plugin.version>3.1.1</maven.assembly.plugin.version>
10.  
    <!-- sdk -->
11.  
    <java.version>1.8</java.version>
12.  
    <scala.version>2.12.13</scala.version>
13.  
    <scala.binary.version>2.12</scala.binary.version>
14.  
    <!-- engine-->
15.  
    <hadoop.version>2.9.2</hadoop.version>
16.  
    <flink.version>1.12.2</flink.version>
17.  
    <hoodie.version>0.9.0</hoodie.version>
18.  
    <hive.version>2.3.9</hive.version>
19.  
     
20.  
    <!-- <scope.type>provided</scope.type>-->
21.  
    <scope.type>compile</scope.type>
22.  
    </properties>
23.  
     
24.  
    <dependencies>
25.  
    <!-- scala -->
26.  
    <dependency>
27.  
    <groupId>org.scala-lang</groupId>
28.  
    <artifactId>scala-library</artifactId>
29.  
    <version>${scala.version}</version>
30.  
    <scope>${scope.type}</scope>
31.  
    </dependency>
32.  
     
33.  
    <!-- flink Dependency -->
34.  
    <dependency>
35.  
    <groupId>org.apache.flink</groupId>
36.  
    <artifactId>flink-runtime-web_${scala.binary.version}</artifactId>
37.  
    <version>${flink.version}</version>
38.  
    <scope>${scope.type}</scope>
39.  
    </dependency>
40.  
    <dependency>
41.  
    <groupId>org.apache.flink</groupId>
42.  
    <artifactId>flink-core</artifactId>
43.  
    <version>${flink.version}</version>
44.  
    <scope>${scope.type}</scope>
45.  
    </dependency>
46.  
    <dependency>
47.  
    <groupId>org.apache.flink</groupId>
48.  
    <artifactId>flink-scala_${scala.binary.version}</artifactId>
49.  
    <version>${flink.version}</version>
50.  
    <scope>${scope.type}</scope>
51.  
    </dependency>
52.  
    <dependency>
53.  
    <groupId>org.apache.flink</groupId>
54.  
    <artifactId>flink-table-common</artifactId>
55.  
    <version>${flink.version}</version>
56.  
    <scope>${scope.type}</scope>
57.  
    </dependency>
58.  
    <dependency>
59.  
    <groupId>org.apache.flink</groupId>
60.  
    <artifactId>flink-table-api-scala-bridge_${scala.binary.version}</artifactId>
61.  
    <version>${flink.version}</version>
62.  
    <scope>${scope.type}</scope>
63.  
    </dependency>
64.  
    <dependency>
65.  
    <groupId>org.apache.flink</groupId>
66.  
    <artifactId>flink-streaming-scala_${scala.binary.version}</artifactId>
67.  
    <version>${flink.version}</version>
68.  
    <scope>${scope.type}</scope>
69.  
    </dependency>
70.  
    <dependency>
71.  
    <groupId>org.apache.flink</groupId>
72.  
    <artifactId>flink-table-planner-blink_${scala.binary.version}</artifactId>
73.  
    <version>${flink.version}</version>
74.  
    <scope>${scope.type}</scope>
75.  
    </dependency>
76.  
    <dependency>
77.  
    <groupId>org.apache.flink</groupId>
78.  
    <artifactId>flink-clients_${scala.binary.version}</artifactId>
79.  
    <version>${flink.version}</version>
80.  
    <scope>${scope.type}</scope>
81.  
    </dependency>
82.  
    <dependency>
83.  
    <groupId>org.apache.flink</groupId>
84.  
    <artifactId>flink-csv</artifactId>
85.  
    <version>${flink.version}</version>
86.  
    <scope>${scope.type}</scope>
87.  
    </dependency>
88.  
    <dependency>
89.  
    <groupId>org.apache.flink</groupId>
90.  
    <artifactId>flink-json</artifactId>
91.  
    <version>${flink.version}</version>
92.  
    <scope>${scope.type}</scope>
93.  
    </dependency>
94.  
    <dependency>
95.  
    <groupId>org.apache.flink</groupId>
96.  
    <artifactId>flink-orc_${scala.binary.version}</artifactId>
97.  
    <version>${flink.version}</version>
98.  
    <scope>${scope.type}</scope>
99.  
    </dependency>
100.  
     <dependency>
101.  
     <groupId>org.apache.flink</groupId>
102.  
     <artifactId>flink-statebackend-rocksdb_2.11</artifactId>
103.  
     <version>${flink.version}</version>
104.  
     <scope>${scope.type}</scope>
105.  
     </dependency>
106.  
     <dependency>
107.  
     <groupId>org.apache.flink</groupId>
108.  
     <artifactId>flink-sql-connector-kafka_${scala.binary.version}</artifactId>
109.  
     <version>${flink.version}</version>
110.  
     <scope>${scope.type}</scope>
111.  
     </dependency>
112.  
     <dependency>
113.  
     <groupId>org.apache.flink</groupId>
114.  
     <artifactId>flink-statebackend-rocksdb_2.11</artifactId>
115.  
     <version>${flink.version}</version>
116.  
     <scope>${scope.type}</scope>
117.  
     </dependency>
118.  
     <dependency>
119.  
     <groupId>org.apache.flink</groupId>
120.  
     <artifactId>flink-connector-hive_${scala.binary.version}</artifactId>
121.  
     <version>${flink.version}</version>
122.  
     <scope>${scope.type}</scope>
123.  
     </dependency>
124.  
     <dependency>
125.  
     <groupId>com.alibaba.ververica</groupId>
126.  
     <artifactId>flink-sql-connector-mysql-cdc</artifactId>
127.  
     <version>1.2.0</version>
128.  
     <scope>${scope.type}</scope>
129.  
     </dependency>
130.  
      
131.  
     <!-- hudi Dependency -->
132.  
     <dependency>
133.  
     <groupId>org.apache.hudi</groupId>
134.  
     <artifactId>hudi-flink-bundle_${scala.binary.version}</artifactId>
135.  
     <version>${hoodie.version}</version>
136.  
     <scope>${scope.type}</scope>
137.  
     </dependency>
138.  
     <dependency>
139.  
     <groupId>org.apache.hudi</groupId>
140.  
     <artifactId>hudi-flink-client</artifactId>
141.  
     <version>${hoodie.version}</version>
142.  
     <scope>${scope.type}</scope>
143.  
     </dependency>
144.  
      
145.  
     <!-- hadoop Dependency-->
146.  
     <dependency>
147.  
     <groupId>org.apache.hadoop</groupId>
148.  
     <artifactId>hadoop-common</artifactId>
149.  
     <version>${hadoop.version}</version>
150.  
     <scope>${scope.type}</scope>
151.  
     </dependency>
152.  
     <dependency>
153.  
     <groupId>org.apache.hadoop</groupId>
154.  
     <artifactId>hadoop-hdfs</artifactId>
155.  
     <version>${hadoop.version}</version>
156.  
     <scope>${scope.type}</scope>
157.  
     </dependency>
158.  
     <dependency>
159.  
     <groupId>org.apache.hadoop</groupId>
160.  
     <artifactId>hadoop-client</artifactId>
161.  
     <version>${hadoop.version}</version>
162.  
     <scope>${scope.type}</scope>
163.  
     </dependency>
164.  
      
165.  
     <!-- hive Dependency-->
166.  
     <dependency>
167.  
     <groupId>org.apache.hive</groupId>
168.  
     <artifactId>hive-exec</artifactId>
169.  
     <version>${hive.version}</version>
170.  
     <scope>${scope.type}</scope>
171.  
     <exclusions>
172.  
     <exclusion>
173.  
     <groupId>org.apache.logging.log4j</groupId>
174.  
     <artifactId>log4j-slf4j-impl</artifactId>
175.  
     </exclusion>
176.  
     <exclusion>
177.  
     <groupId>org.apache.hive</groupId>
178.  
     <artifactId>hive-llap-tez</artifactId>
179.  
     </exclusion>
180.  
     </exclusions>
181.  
     </dependency>
182.  
     </dependencies>
183.  
      
184.  
     <build>
185.  
     <plugins>
186.  
     <plugin>
187.  
     <groupId>net.alchim31.maven</groupId>
188.  
     <artifactId>scala-maven-plugin</artifactId>
189.  
     <version>${scala.maven.plugin.version}</version>
190.  
     <executions>
191.  
     <execution>
192.  
     <goals>
193.  
     <goal>compile</goal>
194.  
     </goals>
195.  
     </execution>
196.  
     </executions>
197.  
     </plugin>
198.  
     <plugin>
199.  
     <groupId>org.apache.maven.plugins</groupId>
200.  
     <artifactId>maven-assembly-plugin</artifactId>
201.  
     <version>${maven.assembly.plugin.version}</version>
202.  
     <configuration>
203.  
     <descriptorRefs>
204.  
     <descriptorRef>jar-with-dependencies</descriptorRef>
205.  
     </descriptorRefs>
206.  
     </configuration>
207.  
     <executions>
208.  
     <execution>
209.  
     <id>make-assembly</id>
210.  
     <phase>package</phase>
211.  
     <goals>
212.  
     <goal>single</goal>
213.  
     </goals>
214.  
     </execution>
215.  
     </executions>
216.  
     </plugin>
217.  
     </plugins>
218.  
     </build>

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