From 95e2f0fa0769e87cbf77cb8d264c75a6fb198a8d Mon Sep 17 00:00:00 2001
From: hcz <h.cz@qq.com>
Date: Thu, 21 May 2020 18:20:41 +0800
Subject: [PATCH] Add brief docs about apache arrow

---
 docs/en/interfaces/formats.md | 20 ++++++++++++++++----
 1 file changed, 16 insertions(+), 4 deletions(-)

diff --git a/docs/en/interfaces/formats.md b/docs/en/interfaces/formats.md
index 4697fbca7e1..ed411a1b0d4 100644
--- a/docs/en/interfaces/formats.md
+++ b/docs/en/interfaces/formats.md
@@ -37,6 +37,8 @@ The supported formats are:
 | [Avro](#data-format-avro)                                       | ✔     | ✔      |
 | [AvroConfluent](#data-format-avro-confluent)                    | ✔     | ✗      |
 | [Parquet](#data-format-parquet)                                 | ✔     | ✔      |
+| [Arrow](#data-format-arrow)                                     | ✔     | ✔      |
+| [ArrowStream](#data-format-arrow-stream)                        | ✔     | ✔      |
 | [ORC](#data-format-orc)                                         | ✔     | ✗      |
 | [RowBinary](#rowbinary)                                         | ✔     | ✔      |
 | [RowBinaryWithNamesAndTypes](#rowbinarywithnamesandtypes)       | ✔     | ✔      |
@@ -985,9 +987,9 @@ See also [how to read/write length-delimited protobuf messages in popular langua
 
 ## Avro {#data-format-avro}
 
-[Apache Avro](http://avro.apache.org/) is a row-oriented data serialization framework developed within Apache’s Hadoop project.
+[Apache Avro](https://avro.apache.org/) is a row-oriented data serialization framework developed within Apache’s Hadoop project.
 
-ClickHouse Avro format supports reading and writing [Avro data files](http://avro.apache.org/docs/current/spec.html#Object+Container+Files).
+ClickHouse Avro format supports reading and writing [Avro data files](https://avro.apache.org/docs/current/spec.html#Object+Container+Files).
 
 ### Data Types Matching {#data_types-matching}
 
@@ -1009,7 +1011,7 @@ The table below shows supported data types and how they match ClickHouse [data t
 | `long (timestamp-millis)` \*                | [DateTime64(3)](../sql-reference/data-types/datetime.md)                                                              | `long (timestamp-millis)` \* |
 | `long (timestamp-micros)` \*                | [DateTime64(6)](../sql-reference/data-types/datetime.md)                                                              | `long (timestamp-micros)` \* |
 
-\* [Avro logical types](http://avro.apache.org/docs/current/spec.html#Logical+Types)
+\* [Avro logical types](https://avro.apache.org/docs/current/spec.html#Logical+Types)
 
 Unsupported Avro data types: `record` (non-root), `map`
 
@@ -1095,7 +1097,7 @@ SELECT * FROM topic1_stream;
 
 ## Parquet {#data-format-parquet}
 
-[Apache Parquet](http://parquet.apache.org/) is a columnar storage format widespread in the Hadoop ecosystem. ClickHouse supports read and write operations for this format.
+[Apache Parquet](https://parquet.apache.org/) is a columnar storage format widespread in the Hadoop ecosystem. ClickHouse supports read and write operations for this format.
 
 ### Data Types Matching {#data_types-matching-2}
 
@@ -1141,6 +1143,16 @@ $ clickhouse-client --query="SELECT * FROM {some_table} FORMAT Parquet" > {some_
 
 To exchange data with Hadoop, you can use [HDFS table engine](../engines/table-engines/integrations/hdfs.md).
 
+## Arrow {data-format-arrow}
+
+[Apache Arrow](https://arrow.apache.org/) comes with two built-in columnar storage formats. ClickHouse supports read and write operations for these formats.
+
+`Arrow` is Apache Arrow's "file mode" format. It is designed for in-memory random access.
+
+## ArrowStream {data-format-arrow-stream}
+
+`ArrowStream` is Apache Arrow's "stream mode" format. It is designed for in-memory stream processing.
+
 ## ORC {#data-format-orc}
 
 [Apache ORC](https://orc.apache.org/) is a columnar storage format widespread in the Hadoop ecosystem. You can only insert data in this format to ClickHouse.