From d2ef18943c91020e57c239d4a1ef294216edd3c9 Mon Sep 17 00:00:00 2001
From: heibaiying <31504331+heibaiying@users.noreply.github.com>
Date: Tue, 5 Nov 2019 22:10:08 +0800
Subject: [PATCH] =?UTF-8?q?Update=20Flink=E7=8A=B6=E6=80=81=E7=AE=A1?=
 =?UTF-8?q?=E7=90=86=E4=B8=8E=E6=A3=80=E6=9F=A5=E7=82=B9=E6=9C=BA=E5=88=B6?=
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---
 notes/Flink状态管理与检查点机制.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/notes/Flink状态管理与检查点机制.md b/notes/Flink状态管理与检查点机制.md
index 61afbae..cfa0906 100644
--- a/notes/Flink状态管理与检查点机制.md
+++ b/notes/Flink状态管理与检查点机制.md
@@ -21,7 +21,7 @@
 
 相对于其他流计算框架，Flink 一个比较重要的特性就是其支持有状态计算。即你可以将中间的计算结果进行保存，并提供给后续的计算使用：
 
-<div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/flink-stateful-stream.png"/> </div>
+<div align="center"> <img width="500px" src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/flink-stateful-stream.png"/> </div>
 
 
 
@@ -31,7 +31,7 @@
 
 算子状态 (Operator State)：顾名思义，状态是和算子进行绑定的，一个算子的状态不能被其他算子所访问到。官方文档上对 Operator State 的解释是：*each operator state is bound to one parallel operator instance*，所以更为确切的说一个算子状态是与一个并发的算子实例所绑定的，即假设算子的并行度是 2，那么其应有两个对应的算子状态：
 
-<div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/flink-operator-state.png"/> </div>
+<div align="center"> <img width="500px" src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/flink-operator-state.png"/> </div>