Hadoop基础-12-Hive

时间  2021-08-15
标签 java node mysql git github web sql shell 数据库 express 栏目 Hadoop 繁體版
原文   原文链接

源码见：https://github.com/hiszm/hadoop-trainjava

Hive概述

http://hive.apache.org/node

  • Hive是什么

The Apache Hive ™ data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive.mysql

Hive 是一个构建在 Hadoop 之上的数据仓库，它能够将结构化的数据文件映射成表，并提供类 SQL 查询功能，用于查询的 SQL 语句会被转化为 MapReduce 做业，而后提交到 Hadoop 上运行。git

  • 为何要使用Hive
    • MappReduce 编程不便
    • 同时也要RDBMS关系型数据库
    • HDFS上没有schema的概念

(schema就是数据库对象的集合 , 所谓的数据库对象也就是常说的表，索引，视图，存储过程等。)github

  • Hive特色：
  1. 简单、容易 上手 (提供了相似 SQL 的查询语言 HQL)，使得精通 sql 可是不了解 Java 编程的人也能很好地进行大数据分析；
  2. 灵活 性高，底层引擎支持 MR/ Tez /Spark；
  3. 为超大的数据集设计的计算和存储能力，集群扩展容易;
  4. 统一的元数据管理，可与presto／impala／sparksql等 共享 数据；
  5. 执行延迟高，不适合作数据的实时处理，但适合作海量数据的 离线 处理。

Hive体系架构

Hive体系架构

  • client : shell , jdbc, webUI(zeppelin)
  • metastore : 指数据库中的元数据

Hive部署架构

Hive部署架构

Hive与RDBMS的区别

  Hive RDBMS
查询语言 Hive SQL SQL
数据储存 HDFS Raw Device or Local FS
索引 无(支持比较弱) 有
执行 MapReduce、 Tez Excutor
执行时延 高，离线 低 , 在线
数据规模 很是大, 大 小

Hive部署

  • 得到wget hive-1.1.0-cdh5.15.1.tar.gz(url)
  • 解压 tar -zxvf hive-1.1.0-cdh5.15.1.tar.gz -C ~/app/
  • 配置环境变量
export HIVE_HOME=/home/hadoop/app/hive-1.1.0-cdh5.15.1
export PATH=$HIVE_HOME/bin:$PATH
  • 生效 source ~/.bash_profile
[hadoop@hadoop000 app]$ source ~/.bash_profile 
[hadoop@hadoop000 app]$ echo $HIVE_HOME
/home/hadoop/app/hive-1.1.0-cdh5.15.1
  • 修改配置

/conf/hive-env.sh
增长一行
web

/conf/hive-site.xml
添加文件sql

[hadoop@hadoop000 conf]$ cat hive-site.xml 
<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<configuration>
<property>
  <name>javax.jdo.option.ConnectionURL</name>
  <value>jdbc:mysql://hadoop000:3306/hadoop_hive?createDatabaseIfNotExist=true</value>
</property>

<property>
  <name>javax.jdo.option.ConnectionDriverName</name>
  <value>com.mysql.jdbc.Driver</value>
</property>

<property>
  <name>javax.jdo.option.ConnectionUserName</name>
  <value>root</value>
</property>

<property>
  <name>javax.jdo.option.ConnectionPassword</name>
  <value>root</value>
</property>
</configuration>
[hadoop@hadoop000 conf]$
  • MySQL驱动 mysql-connector-java-5.1.27-bin.jar

拷贝到目录home/hadoop/app/hive-1.1.0-cdh5.15.1/libshell

  • 安装数据库 用yum 安装
[hadoop@hadoop000 lib]$ mysql -uroot -proot
Warning: Using a password on the command line interface can be insecure.
Welcome to the MySQL monitor.  Commands end with ; or \g.
Your MySQL connection id is 2
Server version: 5.6.42 MySQL Community Server (GPL)

Copyright (c) 2000, 2018, Oracle and/or its affiliates. All rights reserved.

Oracle is a registered trademark of Oracle Corporation and/or its
affiliates. Other names may be trademarks of their respective
owners.

Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.

mysql>

Hive快速入门

  • 启动hive
[hadoop@hadoop000 sbin]$ jps
3218 SecondaryNameNode
3048 DataNode
3560 NodeManager
3451 ResourceManager
2940 NameNode
3599 Jps
hive> create database test
    > ;
OK

show tables;

select * from DBS\G;
数据库

mysql> mysql> select * from DBS\G;
*************************** 1. row ***************************
          DB_ID: 1
           DESC: Default Hive database
DB_LOCATION_URI: hdfs://hadoop000:8020/user/hive/warehouse
           NAME: default
     OWNER_NAME: public
     OWNER_TYPE: ROLE
*************************** 2. row ***************************
          DB_ID: 3
           DESC: NULL
DB_LOCATION_URI: hdfs://hadoop000:8020/user/hive/warehouse/hive.db
           NAME: hive
     OWNER_NAME: hadoop
     OWNER_TYPE: USER
*************************** 3. row ***************************
          DB_ID: 4
           DESC: NULL
DB_LOCATION_URI: hdfs://hadoop000:8020/test/location
           NAME: hive2
     OWNER_NAME: hadoop
     OWNER_TYPE: USER
*************************** 4. row ***************************
          DB_ID: 6
           DESC: NULL
DB_LOCATION_URI: hdfs://hadoop000:8020/user/hive/warehouse/test.db
           NAME: test
     OWNER_NAME: hadoop
     OWNER_TYPE: USER
4 rows in set (0.00 sec)

ERROR: 
No query specified

Hive DDL

Hive DDL=Hive Data Definition Languageexpress

数据库操做

  • Create Database
CREATE (DATABASE|SCHEMA) [IF NOT EXISTS] database_name
  [COMMENT database_comment]
  [LOCATION hdfs_path]
  [MANAGEDLOCATION hdfs_path]
  [WITH DBPROPERTIES (property_name=property_value, ...)];

Drop Database

DROP (DATABASE|SCHEMA) [IF EXISTS] database_name [RESTRICT|CASCADE];
hive> create DATABASE hive_test;
OK
Time taken: 0.154 seconds
hive>

再HDFS上的 默认路径 /user/hive/warehouse/hive_test.db
默认的hive数据库没有default.db的路径/user/hive/warehouse/

自定义建立路径

hive> create DATABASE hive_test2 LOCATION '/test/hive'
    > ;
OK
Time taken: 0.119 seconds
hive> 


[hadoop@hadoop000 network-scripts]$ hadoop fs -ls /test/
Found 1 items
drwxr-xr-x   - hadoop supergroup          0 2020-09-09 06:29 /test/hive

自定义参数

DESC DATABASE [EXTENDED] db_name; --EXTENDED 表示是否显示额外属性
hive> create DATABASE hive_test3 LOCATION '/test/hive'
    > with DBPROPERTIES('creator'='jack');
OK
Time taken: 0.078 seconds
hive> desc database hive_test3
    > ;
OK
hive_test3		hdfs://hadoop000:8020/test/hive	hadoop	USER	
Time taken: 0.048 seconds, Fetched: 1 row(s)
hive> desc database extended hive_test3;
OK
hive_test3		hdfs://hadoop000:8020/test/hive	hadoop	USER	{creator=jack}
Time taken: 0.018 seconds, Fetched: 1 row(s)
hive>

显示当前目录

hive> set hive.cli.print.current.db;
hive.cli.print.current.db=false
hive> set hive.cli.print.current.db=true;
hive (default)>
  • Drop Database
DROP (DATABASE|SCHEMA) [IF EXISTS] database_name [RESTRICT|CASCADE];
hive (default)> show databases;
OK
default
hive
hive2
hive_test
hive_test3
test
Time taken: 0.02 seconds, Fetched: 6 row(s)
hive (default)> drop database hive_test3;
OK
Time taken: 0.099 seconds
hive (default)> show databases;
OK
default
hive
hive2
hive_test
test
Time taken: 0.019 seconds, Fetched: 5 row(s)
hive (default)>
  • 查找数据库
hive (default)> show databases like 'hive*';
OK
hive
hive2
hive_test
Time taken: 0.024 seconds, Fetched: 3 row(s)
hive (default)>
  • 使用数据库
USE database_name;

表操做

  • 建立表
CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [db_name.]table_name     --表名
  [(col_name data_type [COMMENT col_comment],
    ... [constraint_specification])]  --列名 列数据类型
  [COMMENT table_comment]   --表描述
  [PARTITIONED BY (col_name data_type [COMMENT col_comment], ...)]  --分区表分区规则
  [
    CLUSTERED BY (col_name, col_name, ...) 
   [SORTED BY (col_name [ASC|DESC], ...)] INTO num_buckets BUCKETS
  ]  --分桶表分桶规则
  [SKEWED BY (col_name, col_name, ...) ON ((col_value, col_value, ...), (col_value, col_value, ...), ...)  
   [STORED AS DIRECTORIES] 
  ]  --指定倾斜列和值
  [
   [ROW FORMAT row_format]    
   [STORED AS file_format]
     | STORED BY 'storage.handler.class.name' [WITH SERDEPROPERTIES (...)]  
  ]  -- 指定行分隔符、存储文件格式或采用自定义存储格式
  [LOCATION hdfs_path]  -- 指定表的存储位置
  [TBLPROPERTIES (property_name=property_value, ...)]  --指定表的属性
  [AS select_statement];   --从查询结果建立表
CREATE TABLE emp(
empno int ,
ename string,
job string,
mgr int,
hiredate string,
sal double,
comm double,
deptno int
) ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t';
hive> CREATE TABLE emp(
    > empno int ,
    > ename string,
    > job string,
    > mgr int,
    > hiredate string,
    > sal double,
    > comm double,
    > deptno int
    > ) ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t';
OK
Time taken: 0.115 seconds
hive> desc formatted emp;
OK
# col_name            	data_type           	comment             
	 	 
empno               	int                 	                    
ename               	string              	                    
job                 	string              	                    
mgr                 	int                 	                    
hiredate            	string              	                    
sal                 	double              	                    
comm                	double              	                    
deptno              	int                 	                    
	 	 
# Detailed Table Information	 	 
Database:           	hive                	 
Owner:              	hadoop              	 
CreateTime:         	Wed Sep 09 09:34:57 CST 2020	 
LastAccessTime:     	UNKNOWN             	 
Protect Mode:       	None                	 
Retention:          	0                   	 
Location:           	hdfs://hadoop000:8020/user/hive/warehouse/hive.db/emp	 
Table Type:         	MANAGED_TABLE       	 
Table Parameters:	 	 
	transient_lastDdlTime	1599615297          
	 	 
# Storage Information	 	 
SerDe Library:      	org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe	 
InputFormat:        	org.apache.hadoop.mapred.TextInputFormat	 
OutputFormat:       	org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat	 
Compressed:         	No                  	 
Num Buckets:        	-1                  	 
Bucket Columns:     	[]                  	 
Sort Columns:       	[]                  	 
Storage Desc Params:	 	 
	field.delim         	\t                  
	serialization.format	\t                  
Time taken: 0.131 seconds, Fetched: 34 row(s)
  • 加载数据

用DML的加载数据

LOAD DATA [LOCAL] INPATH 'filepath' [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)]
 
LOAD DATA [LOCAL] INPATH 'filepath' [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)] [INPUTFORMAT 'inputformat' SERDE 'serde'] (3.0 or later)

LOAD DATA LOCAL INPATH '/home/hadoop/data/emp.txt' OVERWRITE INTO TABLE emp;

hive> LOAD DATA LOCAL INPATH  '/home/hadoop/data/emp.txt' OVERWRITE INTO TABLE emp; 
Loading data to table hive.emp
Table hive.emp stats: [numFiles=1, totalSize=700]
OK
Time taken: 2.482 seconds
hive> select * from emp;
OK
7369	SMITH	CLERK	7902	1980-12-17	800.0	NULL	20
7499	ALLEN	SALESMAN	7698	1981-2-20	1600.0	300.0	30
7521	WARD	SALESMAN	7698	1981-2-22	1250.0	500.0	30
7566	JONES	MANAGER	7839	1981-4-2	2975.0	NULL	20
7654	MARTIN	SALESMAN	7698	1981-9-28	1250.0	1400.0	30
7698	BLAKE	MANAGER	7839	1981-5-1	2850.0	NULL	30
7782	CLARK	MANAGER	7839	1981-6-9	2450.0	NULL	10
7788	SCOTT	ANALYST	7566	1987-4-19	3000.0	NULL	20
7839	KING	PRESIDENT	NULL	1981-11-17	5000.0	NULL	10
7844	TURNER	SALESMAN	7698	1981-9-8	1500.0	0.0	30
7876	ADAMS	CLERK	7788	1987-5-23	1100.0	NULL	20
7900	JAMES	CLERK	7698	1981-12-3	950.0	NULL	30
7902	FORD	ANALYST	7566	1981-12-3	3000.0	NULL	20
7934	MILLER	CLERK	7782	1982-1-23	1300.0	NULL	10
8888	HIVE	PROGRAM	7839	1988-1-23	10300.0	NULL	NULL
Time taken: 0.363 seconds, Fetched: 15 row(s)
hive>
  • 更改表名
ALTER TABLE table_name RENAME TO new_table_name;

Hive DML

Hive Data Manipulation Language

LOAD DATA [LOCAL] INPATH 'filepath' [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)]
 
LOAD DATA [LOCAL] INPATH 'filepath' [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)] [INPUTFORMAT 'inputformat' SERDE 'serde'] (3.0 or later)

  • LOCAL: 有 就是从服务器目录获取文件, 无则从HDFS系统

  • OVERWRITE: 有 表示新建数据 ; 无 表示追加数据

  • INPATH

    • a relative path, such as project/data1
    • an absolute path, such as /user/hive/project/data1
    • a full URI with scheme and (optionally) an authority, such as hdfs://namenode:9000/user/hive/project/data1

建立查询表create table emp_1 as select * from emp;

  • 导出数据
INSERT OVERWRITE LOCAL DIRECTORY '/tmp/hive'
ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
select empno , ename ,sal,deptno from emp;
hive> 
    > INSERT OVERWRITE LOCAL DIRECTORY '/tmp/hive'
    > ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
    > select empno , ename ,sal,deptno from emp;
Query ID = hadoop_20200909102020_aeb2ef7d-cf18-4bcb-b903-8c6ea1719626
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_1599583423179_0001, Tracking URL = http://hadoop000:8088/proxy/application_1599583423179_0001/
Kill Command = /home/hadoop/app/hadoop-2.6.0-cdh5.15.1/bin/hadoop job  -kill job_1599583423179_0001
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0
2020-09-09 10:21:18,074 Stage-1 map = 0%,  reduce = 0%
2020-09-09 10:21:29,109 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 5.64 sec
MapReduce Total cumulative CPU time: 5 seconds 640 msec
Ended Job = job_1599583423179_0001
Copying data to local directory /tmp/hive
MapReduce Jobs Launched: 
Stage-Stage-1: Map: 1   Cumulative CPU: 5.64 sec   HDFS Read: 4483 HDFS Write: 313 SUCCESS
Total MapReduce CPU Time Spent: 5 seconds 640 msec
OK
Time taken: 35.958 seconds
hive> 

[hadoop@hadoop000 hive]$ cat 000000_0 
7369	SMITH	800.0	20
7499	ALLEN	1600.0	30
7521	WARD	1250.0	30
7566	JONES	2975.0	20
7654	MARTIN	1250.0	30
7698	BLAKE	2850.0	30
7782	CLARK	2450.0	10
7788	SCOTT	3000.0	20
7839	KING	5000.0	10
7844	TURNER	1500.0	30
7876	ADAMS	1100.0	20
7900	JAMES	950.0	30
7902	FORD	3000.0	20
7934	MILLER	1300.0	10
8888	HIVE	10300.0	\N
[hadoop@hadoop000 hive]$

Hive QL

  • 基本统计

和普通的sql并没有两样

select * from emp where deptno=10;

  • 聚合函数

像这种聚合(max,min,avg,sum)函数就是要跑mappreduce的

hive> select count(1) from emp where deptno=10;
Query ID = hadoop_20200909104949_1ce185de-2025-4633-9324-3e47f30fb157
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks determined at compile time: 1
In order to change the average load for a reducer (in bytes):
  set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
  set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
  set mapreduce.job.reduces=<number>
Starting Job = job_1599583423179_0002, Tracking URL = http://hadoop000:8088/proxy/application_1599583423179_0002/
Kill Command = /home/hadoop/app/hadoop-2.6.0-cdh5.15.1/bin/hadoop job  -kill job_1599583423179_0002
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1
2020-09-09 10:50:00,361 Stage-1 map = 0%,  reduce = 0%
2020-09-09 10:50:10,092 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 6.52 sec
2020-09-09 10:50:25,233 Stage-1 map = 100%,  reduce = 100%, Cumulative CPU 11.72 sec
MapReduce Total cumulative CPU time: 11 seconds 720 msec
Ended Job = job_1599583423179_0002
MapReduce Jobs Launched: 
Stage-Stage-1: Map: 1  Reduce: 1   Cumulative CPU: 11.72 sec   HDFS Read: 9708 HDFS Write: 2 SUCCESS
Total MapReduce CPU Time Spent: 11 seconds 720 msec
OK
3
Time taken: 38.666 seconds, Fetched: 1 row(s)
hive> select * from emp where deptno=10;
OK
7782	CLARK	MANAGER	7839	1981-6-9	2450.0	NULL	10
7839	KING	PRESIDENT	NULL	1981-11-17	5000.0	NULL	10
7934	MILLER	CLERK	7782	1982-1-23	1300.0	NULL	10
Time taken: 0.209 seconds, Fetched: 3 row(s)
hive>
  • 分组函数

select deptno , avg(sal) from group by deptno;
注意select的字段没有再聚合函数就要出现再group by 里面

  • join的使用

用于涉及到多表

CREATE TABLE dept(
deptno int,
dname string,
loc string
)ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t';

LOAD DATA LOCAL INPATH '/home/hadoop/data/dept.txt' OVERWRITE INTO TABLE dept;

select e.empno,e.ename,e.sal,e.deptno,d.dname
from emp e join dept d
on e.deptno=d.deptno;
hive> select e.empno,e.ename,e.sal,e.deptno,d.dname
    > from emp e join dept d
    > on e.deptno=d.deptno;
Query ID = hadoop_20200909140808_8635204d-8e8a-4267-8503-ef242f022ebc
Total jobs = 1
2020-09-09 02:08:51	Starting to launch local task to process map join;	maximum memory = 477626368
2020-09-09 02:08:54	End of local task; Time Taken: 3.023 sec.
Execution completed successfully
MapredLocal task succeeded
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_1599583423179_0004, Tracking URL = http://hadoop000:8088/proxy/application_1599583423179_0004/
Kill Command = /home/hadoop/app/hadoop-2.6.0-cdh5.15.1/bin/hadoop job  -kill job_1599583423179_0004
Hadoop job information for Stage-3: number of mappers: 1; number of reducers: 0
2020-09-09 14:09:06,852 Stage-3 map = 0%,  reduce = 0%
2020-09-09 14:09:18,823 Stage-3 map = 100%,  reduce = 0%, Cumulative CPU 6.7 sec
MapReduce Total cumulative CPU time: 6 seconds 700 msec
Ended Job = job_1599583423179_0004
MapReduce Jobs Launched: 
Stage-Stage-3: Map: 1   Cumulative CPU: 6.7 sec   HDFS Read: 7649 HDFS Write: 406 SUCCESS
Total MapReduce CPU Time Spent: 6 seconds 700 msec
OK
7369	SMITH	800.0	20	RESEARCH
7499	ALLEN	1600.0	30	SALES
7521	WARD	1250.0	30	SALES
7566	JONES	2975.0	20	RESEARCH
7654	MARTIN	1250.0	30	SALES
7698	BLAKE	2850.0	30	SALES
7782	CLARK	2450.0	10	ACCOUNTING
7788	SCOTT	3000.0	20	RESEARCH
7839	KING	5000.0	10	ACCOUNTING
7844	TURNER	1500.0	30	SALES
7876	ADAMS	1100.0	20	RESEARCH
7900	JAMES	950.0	30	SALES
7902	FORD	3000.0	20	RESEARCH
7934	MILLER	1300.0	10	ACCOUNTING
Time taken: 46.765 seconds, Fetched: 14 row(s)
hive>
  • 执行计划

explain
select e.empno,e.ename,e.sal,e.deptno,d.dname
from emp e join dept d
on e.deptno=d.deptno;
hive> explain
    > select e.empno,e.ename,e.sal,e.deptno,d.dname
    > from emp e join dept d
    > on e.deptno=d.deptno;
OK
STAGE DEPENDENCIES:
  Stage-4 is a root stage
  Stage-3 depends on stages: Stage-4
  Stage-0 depends on stages: Stage-3

STAGE PLANS:
  Stage: Stage-4
    Map Reduce Local Work
      Alias -> Map Local Tables:
        d 
          Fetch Operator
            limit: -1
      Alias -> Map Local Operator Tree:
        d 
          TableScan
            alias: d
            Statistics: Num rows: 1 Data size: 79 Basic stats: COMPLETE Column stats: NONE
            Filter Operator
              predicate: deptno is not null (type: boolean)
              Statistics: Num rows: 1 Data size: 79 Basic stats: COMPLETE Column stats: NONE
              HashTable Sink Operator
                keys:
                  0 deptno (type: int)
                  1 deptno (type: int)

  Stage: Stage-3
    Map Reduce
      Map Operator Tree:
          TableScan
            alias: e
            Statistics: Num rows: 6 Data size: 700 Basic stats: COMPLETE Column stats: NONE
            Filter Operator
              predicate: deptno is not null (type: boolean)
              Statistics: Num rows: 3 Data size: 350 Basic stats: COMPLETE Column stats: NONE
              Map Join Operator
                condition map:
                     Inner Join 0 to 1
                keys:
                  0 deptno (type: int)
                  1 deptno (type: int)
                outputColumnNames: _col0, _col1, _col5, _col7, _col12
                Statistics: Num rows: 3 Data size: 385 Basic stats: COMPLETE Column stats: NONE
                Select Operator
                  expressions: _col0 (type: int), _col1 (type: string), _col5 (type: double), _col7 (type: int), _col12 (type: string)
                  outputColumnNames: _col0, _col1, _col2, _col3, _col4
                  Statistics: Num rows: 3 Data size: 385 Basic stats: COMPLETE Column stats: NONE
                  File Output Operator
                    compressed: false
                    Statistics: Num rows: 3 Data size: 385 Basic stats: COMPLETE Column stats: NONE
                    table:
                        input format: org.apache.hadoop.mapred.TextInputFormat
                        output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
                        serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
      Local Work:
        Map Reduce Local Work

  Stage: Stage-0
    Fetch Operator
      limit: -1
      Processor Tree:
        ListSink

 

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