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new 647272848 [ISSUE #460]Fix 30RocketMQ Streams Overview.md document
pictures not display (#461)
647272848 is described below
commit 6472728485bb82373f644fb98f9f93e5da175ffd
Author: mxsm <[email protected]>
AuthorDate: Thu Jan 19 12:20:56 2023 +0800
[ISSUE #460]Fix 30RocketMQ Streams Overview.md document pictures not
display (#461)
---
.../version-5.0/07-streams/30RocketMQ Streams Overview.md | 10 +++++-----
1 file changed, 5 insertions(+), 5 deletions(-)
diff --git
a/i18n/en/docusaurus-plugin-content-docs/version-5.0/07-streams/30RocketMQ
Streams Overview.md
b/i18n/en/docusaurus-plugin-content-docs/version-5.0/07-streams/30RocketMQ
Streams Overview.md
index c959eec42..794797ac4 100644
--- a/i18n/en/docusaurus-plugin-content-docs/version-5.0/07-streams/30RocketMQ
Streams Overview.md
+++ b/i18n/en/docusaurus-plugin-content-docs/version-5.0/07-streams/30RocketMQ
Streams Overview.md
@@ -4,18 +4,18 @@ RocketMQ Streams is a lightweight stream computing engine
based on RocketMQ. It
## Architecture
-
+
Data is consumed from RocketMQ by RocketMQ-streams, processed, and ultimately
written back to RocketMQ.
-
+
Data is consumed by the RocketMQ Consumer, enters the processing topology to
be processed by operators. If the stream processing task contains the keyBy
operator, the data needs to be grouped by Key and written to a shuffle topic.
Subsequent operators consume from the shuffle topic. If there are also stateful
operators such as count, the calculation requires reading and writing to the
state topic. After the calculation is finished, the result is written back to
RocketMQ.
## Consume model
-
+
The calculation instances actually depend on the client of the Rocket-streams
SDK. Therefore, the calculation instances consume MQ, dependent on the RocketMQ
rebalance allocation. The total number of calculation instances cannot be
greater than the total number of consuming MQ, otherwise, some calculation
instances will be in a waiting state, unable to consume data.
@@ -23,13 +23,13 @@ One calculation instance can consume multiple MQs, and
within one instance, ther
## Status
-
+
For stateful operators, such as count, grouping must be done first before
summing. The grouping operator keyBy will re-write the data to RocketMQ based
on the grouping key, and ensures that data with the same key is written to the
same partition (this process is called shuffle), to ensure that data with the
same key is consumed by the same consumer. The state is locally accelerated by
RocksDB, and remotely persisted by RocketMQ.
## Expansion/shrinkage capacity
-
+
When the calculation instances are reduced from 3 to 2, with the help of the
rebalance function under the RocketMQ cluster consumption mode, the consumed MQ
will be re-allocated among the calculation instances. The MQ2 and MQ3 consumed
by Instance1 are allocated to Instance2 and Instance3, and the state data of
these two MQs also needs to be migrated to Instance2 and Instance3. This also
implies that the state data is saved according to the original data partition
MQ; expansion is just t [...]