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9.27学习笔记

news 2026/6/15 9:44:10

今日速览
环境拓扑（安全开启后）
表格
节点新增角色 Principal 样例
node1 KDC (kerberos) kadmin/admin@HADOOP.COM
node2 YARN RM + Queue Mgmt yarn/node2@HADOOP.COM
node3 Phoenix RS hbase/node3@HADOOP.COM
关键知识点
3.1 Kerberos 流程
Client → AS 获取 TGT
TGT → TGS 获取 Service Ticket
Service Ticket → Hadoop NameNode 完成 SASL 握手
3.2 YARN Capacity 调度器
层级队列：root → prod/dev → 子队列 spark/flink
抢占：当 prod 空闲资源 < 10 % 且 dev 占用 > 20 % 时触发
用户限额：yarn.scheduler.capacity.root.dev.maximum-user-limit-factor=0.5
3.3 Phoenix 索引
全局索引（Global Index）= 新表，覆盖列减少回表
本地索引（Local Index）= 同 Region，前缀过滤高效
写放大：WAL + Index 表双写，可调 phoenix.index.wal.disabled=true（容忍宕机丢数据）
3.4 数据仓库拉链表
关链 end_date = 当天-1，开链 start_date = 当天
Hive SQL 用 row_number() over (partition by user_id order by ts) 去重
实操流水
4.1 Kerberos 安装
bash

node1

yum -y install krb5-server krb5-workstation
vim /var/kerberos/krb5kdc/kdc.conf # realms = HADOOP.COM
kdb5_util create -s
systemctl enable --now krb5kdc kadmin

创建主体

kadmin.local -q "addprinc -randkey hdfs/node1@HADOOP.COM"
kadmin.local -q "xst -k /etc/security/keytabs/hdfs.service.keytab hdfs/node1@HADOOP.COM"

分发 keytab 并 chmod 400

4.2 Hadoop 开启安全
xml

hadoop.security.authenticationkerberos hadoop.security.authorizationtrue xmldfs.block.access.token.enabletrue dfs.datanode.data.dir.perm700 启动顺序： kinit -kt /etc/security/keytabs/hdfs.service.keytab hdfs/node1@HADOOP.COM start-dfs.sh 验证：无 ticket 时 hdfs dfs -ls / → Permission denied (user=root, code=401) 4.3 YARN Capacity 队列yarn.scheduler.capacity.root.queuesprod,devyarn.scheduler.capacity.root.prod.capacity70yarn.scheduler.capacity.root.dev.capacity30yarn.scheduler.capacity.root.dev.maximum-allocation-vcores4yarn.scheduler.capacity.root.prod.user-limit-factor1yarn.scheduler.capacity.root.prod.stateRUNNINGyarn.scheduler.capacity.root.dev.stateRUNNINGyarn.scheduler.capacity.root.prod.acl_submit_applicationsprodyarn.scheduler.capacity.root.dev.acl_submit_applicationsdev 刷新： yarn rmadmin -refreshQueues 提交到 dev： spark-submit --master yarn --queue dev --class ... 4.4 Phoenix 索引实验 sql -- 建订单主表 CREATE TABLE ORDERS (id VARCHAR PRIMARY KEY,user_id VARCHAR,amount DECIMAL,ts BIGINT ) SALT_BUCKETS=6;

-- 写 1000 w 行
upsert into orders select ...

-- 无索引查询
select * from orders where user_id='u1234'; -- 14.2 s 全表

-- 建全局索引
CREATE INDEX idx_user ON ORDERS(user_id) INCLUDE(amount);

-- 同样查询 1.1 s，Explain 显示 RANGE SCAN OVER idx_user
写入 10 w 行测试：
– 无主索引 6.8 s
– 有主索引 7.3 s
吞吐下降 ≈ 7 %，可接受。
4.5 数据仓库分层
ODS 层（原始）

CREATE EXTERNAL TABLE ods.user_log(
user_id STRING,
event_type STRING,
ts BIGINT,
json STRING
) STORED AS TEXTFILE
LOCATION '/data/ods/user_log/';
load data inpath '/tmp/user_log_20250924.txt' into table ods.user_log;
DWD 层（清洗拉链）
sql

WITH tmp AS (
SELECT *, row_number() over (partition by user_id order by ts desc) rn
FROM ods.user_log
)
INSERT OVERWRITE TABLE dwd.user_log_chain
SELECT user_id, event_type, ts, '2025-09-24' start_date, '9999-12-31' end_date
FROM tmp WHERE rn=1;
DWS 层（日活宽表）

CREATE TABLE dws.user_daily (
dt STRING,
user_id STRING,
first_event STRING,
last_event STRING,
event_cnt INT
) STORED AS ORC;

INSERT OVERWRITE TABLE dws.user_daily PARTITION(dt='2025-09-24')
SELECT '2025-09-24', user_id, min(event_type), max(event_type), count(*)
FROM dwd.user_log_chain
WHERE start_date<='2025-09-24' AND end_date>='2025-09-24'
GROUP BY user_id;
结果：1 GB 原始 → 350 MB 宽表。
4.6 差异快照 & 滚动删除
bash