Omega359 commented on code in PR #58:
URL: https://github.com/apache/datafusion-site/pull/58#discussion_r1989483657
##########
content/blog/2025-03-11-ordering-analysis.md:
##########
@@ -0,0 +1,381 @@
+---
+layout: post
+title: Using Ordering for Better Plans in Apache DataFusion
+date: 2025-03-11
+author: Mustafa Akur, Andrew Lamb
+categories: [tutorial]
+---
+
+<!--
+{% comment %}
+Licensed to the Apache Software Foundation (ASF) under one or more
+contributor license agreements. See the NOTICE file distributed with
+this work for additional information regarding copyright ownership.
+The ASF licenses this file to you under the Apache License, Version 2.0
+(the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+{% endcomment %}
+-->
+
+<!-- see https://github.com/apache/datafusion/issues/11631 for details -->
+
+## Introduction
+In this blog post, we explain when an ordering requirement of an operator is
satisfied by its input data. This analysis is essential for order-based
optimizations and is often more complex than one might initially think.
+<blockquote style="border-left: 4px solid #007bff; padding: 10px;
background-color: #f8f9fa;">
+ <strong>Ordering Requirement</strong> for an operator describes how the
input data to that operator must be sorted for the operator to compute the
correct result. It is the job of the planner to make sure that these
requirements are satisfied during execution (See DataFusion <a
href="https://docs.rs/datafusion/latest/datafusion/physical_optimizer/enforce_sorting/struct.EnforceSorting.html";
target="_blank">EnforceSorting</a> for an implementation of such rule).
+</blockquote>
+
+There are various use cases, where this type of analysis can be useful such as
the following examples.
+### Removing Unnecessary Sorts
+Imagine a user wants to execute the following query:
+```SQL
+SELECT hostname, log_line
+FROM telemetry ORDER BY time ASC limit 10
+```
+If we don't know anything about the `telemetry` table, we need to sort it by
`time ASC` and then retrieve the first 10 rows to get the correct result.
However, if the table is already ordered by `time ASC`, we can simply retrieve
the first 10 rows. This approach executes much faster and uses less memory
compared to resorting the entire table, even when the [TopK] operator is used.
+
+[TopK]:
https://docs.rs/datafusion/latest/datafusion/physical_plan/struct.TopK.html
+
+In order to avoid the sort, the query optimizer must determine the data is
already sorted. For simple queries the analysis is straightforward, but it gets
complicated fast. For example, what if your data is sorted by `[hostname, time
ASC]` and your query is
+```sql
+SELECT hostname, log_line
+FROM telemetry WHERE hostname = 'app.example.com' ORDER BY time ASC;
+```
+In this case, a sort still isn't needed, but the analysis must reason about
the sortedness of the stream when it knows `hostname` has a single value.
+
+### Optimized Operator Implementations
+As another use case, some operators can utilize the ordering information to
change its underlying algorithm to execute more efficiently. Consider the
following query:
+```SQL
+SELECT COUNT(log_line)
+FROM telemetry GROUP BY hostname;
+```
+Most analytic systems, including DataFusion, by default implement such a query
using a hash table keyed on values of `hostname` to store the counts. However,
if the `telemetry` table is sorted by `hostname`, there are much more
efficient algorithms for grouping on `hostname` values than hashing every value
and storing it in memory. However, the more efficient algorithm can only be
used when the input is sorted correctly. To see this in practice, check out the
[source](https://github.com/apache/datafusion/tree/main/datafusion/physical-plan/src/aggregates/order)
for ordered variant of the `Aggregation` in `DataFusion`.
+
+### Streaming-Friendly Execution
+
+Stream processing aims to produce results immediately as they become
available, ensuring minimal latency for real-time workloads. However, some
operators need to consume all input data before producing any output. Consider
the `Sort` operation: before it can start generating output, the algorithm must
first process all input data. As a result, data flow halts whenever such an
operator is encountered until all input is consumed. When a physical query plan
contains such an operator (`Sort`, `CrossJoin`, ..), we refer to this as
pipeline breaking, meaning the query cannot be executed in a streaming fashion.
+
+For a query to be executed in a streaming fashion, we need to satisfy 2
conditions:
+
+**Logically Streamable**
+It should be possible to generate what user wants in streaming fashion.
Consider following query:
+
+```SQL
+SELECT SUM(amount)
+FROM orders
+```
+Here, the user wants to compute the sum of all amounts in the orders table. By
nature, this query requires scanning the entire table to generate a result,
making it impossible to execute in a streaming fashion.
+
+**Streaming Aware Planner**
+Being logically streamable does not guarantee that a query will execute in a
streaming fashion. SQL is a declarative language, meaning it specifies 'WHAT'
user wants. It is up to the planner, 'HOW' to generate the result. In most
cases, there are many ways to compute the correct result for a given query. The
query planner is responsible for choosing "a way" (ideally the best<sup
id="optimal1">[*](#optimal)</sup> one) among the all alternatives to generate
what user asks for. If a plan contains a pipeline-breaking operator, the
execution will not be streaming—even if the query is logically streamable. To
generate truly streaming plans from logically streamable queries, the planner
must carefully analyze the existing orderings in the source tables to ensure
that the final plan does not contain any pipeline-breaking operators.
Review Comment:
```suggestion
Being logically streamable does not guarantee that a query will execute in a
streaming fashion. SQL is a declarative language, meaning it specifies 'WHAT'
user wants. It is up to the planner 'HOW' to generate the result. In most cases
there are many ways to compute the correct result for a given query. The query
planner is responsible for choosing "a way" (ideally the best<sup
id="optimal1">[*](#optimal)</sup> one) among the all alternatives to generate
what user asks for. If a plan contains a pipeline-breaking operator the
execution will not be streaming—even if the query is logically streamable. To
generate truly streaming plans from logically streamable queries the planner
must carefully analyze the existing orderings in the source tables to ensure
that the final plan does not contain any pipeline-breaking operators.
```
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
