ivankelly commented on a change in pull request #1466: Topic compaction
documentation
URL: https://github.com/apache/incubator-pulsar/pull/1466#discussion_r191710224
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File path: site/docs/latest/getting-started/ConceptsAndArchitecture.md
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@@ -508,18 +524,55 @@ while (true) {
To create a reader that will read from the latest available message:
```java
-MessageId id = MessageId.latest;
-Reader reader = pulsarClient.createReader(topic, id, new
ReaderConfiguration());
+Reader<byte[]> reader = pulsarClient.newReader()
+ .topic(topic)
+ .startMessageId(MessageId.latest)
+ .create();
```
To create a reader that will read from some message between earliest and
latest:
```java
byte[] msgIdBytes = // Some byte array
MessageId id = MessageId.fromByteArray(msgIdBytes);
-Reader reader = pulsarClient.createReader(topic, id, new
ReaderConfiguration());
+Reader<byte[]> reader = pulsarClient.newReader()
+ .topic(topic)
+ .startMessageId(id)
+ .create();
```
+## Topic compaction {#compaction}
+
+Pulsar was built with highly scalable [persistent
storage](#persistent-storage) of message data as a primary objective. Pulsar {%
popover topics %} enable you to persistently store as many unacknowledged
messages as you need while preserving message ordering. By default, Pulsar
stores *all* unacknowledged/unprocessed messages produced on a topic.
Accumulating many unacknowledged messages on a topic is necessary for many
Pulsar use cases but it can also be very time intensive for Pulsar {% popover
consumers %} to "rewind" through the entire log of messages.
+
+{% include admonition.html type="success" content="For a more practical guide
to topic compaction, see the [Topic compaction
cookbook](../../cookbooks/compaction)." %}
+
+For some use cases consumers don't need a complete "image" of the topic log.
They may only need a few values to construct a more "shallow" image of the log,
perhaps even just the most recent value. For these kinds of use cases Pulsar
offers **topic compaction**. When you run compaction on a topic, Pulsar goes
through a topic's backlog and removes messages that are *obscured* by later
messages, i.e. it goes through the topic on a per-key basis and leaves only the
most recent message associated with that key.
+
+Pulsar's topic compaction feature:
+
+* Allos for much more efficient "rewind" through topic logs
+* Applies only to [persistent topics](#persistent-storage)
+* Is triggered manually via the command line. See the [Topic compaction
cookbook](../../cookbooks/compaction)
+* Is conceptually and operationally distinct from [retention and
expiry](#message-retention-and-expiry). Topic compaction *does*, however,
respect retention. If retention has removed a message from the message backlog
of a topic, the message will also not be readable from the compacted topic
ledger.
+
+{% include admonition.html type="info" title="Topic compaction example: the
stock ticker"
+ content="An example use case for a compacted Pulsar topic would be a stock
ticker topic. On a stock ticker topic, each message bears a timestamped dollar
value for stocks for purchase (with the message key holding the stock symbol,
e.g. `AAPL` or `GOOG`). With a stock ticker you may care only about the most
recent value(s) of the stock and have no interest in historical data (i.e. you
don't need to construct a complete image of the topic's sequence of messages
per key). Compaction would be highly beneficial in this case because it would
keep consumers from needing to rewind through obscured messages." %}
+
+### How topic compaction works
+
+When topic compaction is triggered [via the CLI](../../cookbooks/compaction),
Pulsar will iterate over the entire topic from beginning to end. For each key
that it encounters the {% popover broker %} responsible will keep a record of
the latest occurrence of that key. When this iterative process is finished, the
broker will create a [BookKeeper ledger](#ledgers) to store the compacted topic.
Review comment:
"broker responsible" -> compaction routine, or instance. It may be the
broker doing this, but that's not really relevant. Compaction is like a
subprocess within the broker if run through REST API, which is why its easy to
run as a separate process.
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