felipecrv commented on code in PR #41593: URL: https://github.com/apache/arrow/pull/41593#discussion_r1631367000
########## docs/source/format/Intro.rst: ########## @@ -0,0 +1,458 @@ +.. 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. + +***************************************** +Introduction to the Arrow Columnar Format Review Comment: Maybe this should be called just "Introduction"  ########## docs/source/format/Intro.rst: ########## @@ -0,0 +1,458 @@ +.. 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. + +***************************************** +Introduction to the Arrow Columnar Format +***************************************** + +Apache Arrow was born with the idea to define a set of standards for +data representation and interchange between languages and systems to +avoid costs of data serialization/deserialization and in order to +avoid reinventing the wheel in each of those systems and languages. + +Each system or language requires their own format definitions, implementation +of common algorithms, etcetera. In our heterogeneous environments we +often have to move data from one system or language to accommodate our +workflows that meant copy and convert the data between them, which is +quite costly. + +Apart from this initial vision, Arrow has grown to also develop a +multi-language collection of libraries for solving problems related to +in-memory analytical data processing. This includes such topics as: + +* Zero-copy shared memory and RPC-based data movement +* Reading and writing file formats (like CSV, `Apache ORC`_, and `Apache Parquet`_) +* In-memory analytics and query processing + +.. _Apache ORC: https://orc.apache.org/ +.. _Apache Parquet: https://parquet.apache.org/ + +Arrow Columnar Format +===================== + Review Comment: I put "tabular" in my suggestions above. ########## docs/source/format/Intro.rst: ########## @@ -0,0 +1,458 @@ +.. 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. + +***************************************** +Introduction to the Arrow Columnar Format +***************************************** + +Apache Arrow was born with the idea to define a set of standards for +data representation and interchange between languages and systems to +avoid costs of data serialization/deserialization and in order to +avoid reinventing the wheel in each of those systems and languages. + +Each system or language requires their own format definitions, implementation +of common algorithms, etcetera. In our heterogeneous environments we +often have to move data from one system or language to accommodate our +workflows that meant copy and convert the data between them, which is +quite costly. + +Apart from this initial vision, Arrow has grown to also develop a +multi-language collection of libraries for solving problems related to +in-memory analytical data processing. This includes such topics as: + +* Zero-copy shared memory and RPC-based data movement +* Reading and writing file formats (like CSV, `Apache ORC`_, and `Apache Parquet`_) +* In-memory analytics and query processing Review Comment: ```md The Apache Arrow specification can be implemented in any programming language but official implementations for many languages are available. An implementation consists of format definitions using the constructs offered by the language and common in-memory data processing algorithms (e.g. slicing and concatenating tables). Users can extend and use the utilities provided by the Apache Arrow implementation in their programming language of choice. Some implementations are further ahead and feature a vast set of algorithms for in-memory analytical data processing. These algorithms can be used directly, via dataframe APIs, or even through relational query languages like SQL. As the format gets more adoption, it becomes easier for data processing systems to exchange tabular data. Among other things, an agreed upon in-memory format, enables the implementations of zero-copy IPC protocols (inter-process communication without copying data in memory) and more efficient reading and writing of file formats like CSV, `Apache ORC`_, and `Apache Parquet`_. ``` ########## docs/source/format/Intro.rst: ########## @@ -0,0 +1,458 @@ +.. 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. + +***************************************** +Introduction to the Arrow Columnar Format +***************************************** + +Apache Arrow was born with the idea to define a set of standards for +data representation and interchange between languages and systems to +avoid costs of data serialization/deserialization and in order to +avoid reinventing the wheel in each of those systems and languages. + +Each system or language requires their own format definitions, implementation +of common algorithms, etcetera. In our heterogeneous environments we +often have to move data from one system or language to accommodate our +workflows that meant copy and convert the data between them, which is +quite costly. + +Apart from this initial vision, Arrow has grown to also develop a +multi-language collection of libraries for solving problems related to +in-memory analytical data processing. This includes such topics as: + +* Zero-copy shared memory and RPC-based data movement +* Reading and writing file formats (like CSV, `Apache ORC`_, and `Apache Parquet`_) +* In-memory analytics and query processing + +.. _Apache ORC: https://orc.apache.org/ +.. _Apache Parquet: https://parquet.apache.org/ + +Arrow Columnar Format +===================== + +.. figure:: ./images/columnar-diagram_1.svg + :scale: 70% + :alt: Diagram with tabular data of 4 rows and columns. + +Data can be represented in memory using a row based format or a column Review Comment: This reads like "data in an arrow table". Perhaps a sub-section discussing row-by-row and column-by-column should be added before the "Arrow Columnar Format" section can focus solely on the columnar arrow format. ########## docs/source/format/Intro.rst: ########## @@ -0,0 +1,458 @@ +.. 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. + +***************************************** +Introduction to the Arrow Columnar Format +***************************************** + +Apache Arrow was born with the idea to define a set of standards for +data representation and interchange between languages and systems to +avoid costs of data serialization/deserialization and in order to +avoid reinventing the wheel in each of those systems and languages. Review Comment: Suggestions. Feel free to tweak and improve. I tried to break the paragraph in shorter phrases and: 1. be specific about "tabular" (as there are many formats for non-tabular data interchange) 2. replaced "reinventing the wheel" with "implementation cost" ```suggestion Apache Arrow was born from the need for a set of standards around tabular data representation and interchange between systems. The adoption of these standards reduce computing costs of data serialization/deserialization and implementation costs across systems implemented in different programming languages. ``` -- 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]
