Merge pull request #3507 from Blargian/enable_MD010

Enable MD010 (no hard-tabs)

Author: Blargian

docs/_snippets/_S3_authentication_and_bucket.md

@@ -111,22 +111,22 @@ The bucket name must be unique across AWS, not just the organization, or it will
 12. Add a bucket policy, example below:
 ```json
 {
-	"Version": "2012-10-17",
-	"Id": "Policy123456",
-	"Statement": [
-		{
-			"Sid": "abc123",
-			"Effect": "Allow",
-			"Principal": {
-				"AWS": "arn:aws:iam::921234567898:user/mars-s3-user"
-			},
-			"Action": "s3:*",
-			"Resource": [
-				"arn:aws:s3:::mars-doc-test",
-				"arn:aws:s3:::mars-doc-test/*"
-			]
-		}
-	]
+  "Version" : "2012-10-17",
+  "Id" : "Policy123456",
+  "Statement" : [
+    {
+      "Sid" : "abc123",
+      "Effect" : "Allow",
+      "Principal" : {
+        "AWS" : "arn:aws:iam::921234567898:user/mars-s3-user"
+      },
+      "Action" : "s3:*",
+      "Resource" : [
+        "arn:aws:s3:::mars-doc-test",
+        "arn:aws:s3:::mars-doc-test/*"
+      ]
+    }
+  ]
 }
 ```
 

docs/about-us/adopters.md

@@ -118,7 +118,7 @@ The following list of companies using ClickHouse and their success stories is as
 | [Common Room](https://www.commonroom.io/) | Marketing SaaS | Real-Time Analytics | — | — | [Seattle Meetup, March 2024](https://www.youtube.com/watch?v=liTgGiTuhJE) |
 | [Constructor](https://constructor.io/) | E-commerce Search | E-commerce Search | — | — | ClickHouse Cloud user |
 | [Contentsquare](https://contentsquare.com) | Web analytics | Main product | — | — | [Meetup Video, January 2023](https://www.youtube.com/watch?v=zvuCBAl2T0Q&list=PL0Z2YDlm0b3iNDUzpY1S3L_iV4nARda_U&index=5) [Blog Post, October 2022](https://clickhouse.com/blog/contentsquare-migration-from-elasticsearch-to-clickhouse) [Blog post in French, November 2018](http://souslecapot.net/2018/11/21/patrick-chatain-vp-engineering-chez-contentsquare-penser-davantage-amelioration-continue-que-revolution-constante/) |
-| [Coroot](https://coroot.com/) | Software & Technology	 | Observability | — | — | [Twitter, July 2023](https://twitter.com/coroot_com/status/1680993372385804288?s=20) |
+| [Coroot](https://coroot.com/) | Software & Technology  | Observability | — | — | [Twitter, July 2023](https://twitter.com/coroot_com/status/1680993372385804288?s=20) |
 | [Corsearch](https://corsearch.com/) | Marketing SaaS (Brand Protection) | Main Datastore | — | — | [Seattle Meetup, March 2023](https://www.youtube.com/watch?v=BuS8jFL9cvw&list=PL0Z2YDlm0b3iNDUzpY1S3L_iV4nARda_U&index=10) |
 | [Corunet](https://coru.net/) | Analytics | Main product | — | — | [Slides in English, April 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup21/predictive_models.pdf) |
 | [Covalent](https://www.covalenthq.com/) | Financial - Crypto | Blockchain analysis | — | — | ClickHouse Cloud user |

docs/chdb/guides/querying-parquet.md

@@ -64,15 +64,15 @@ chdb.query(query, 'TabSeparated')
 ```
 
 ```text
-num_columns	UInt64
-num_rows	UInt64
-num_row_groups	UInt64
-format_version	String
-metadata_size	UInt64
-total_uncompressed_size	UInt64
-total_compressed_size	UInt64
-columns	Array(Tuple(name String, path String, max_definition_level UInt64, max_repetition_level UInt64, physical_type String, logical_type String, compression String, total_uncompressed_size UInt64, total_compressed_size UInt64, space_saved String, encodings Array(String)))
-row_groups	Array(Tuple(num_columns UInt64, num_rows UInt64, total_uncompressed_size UInt64, total_compressed_size UInt64, columns Array(Tuple(name String, path String, total_compressed_size UInt64, total_uncompressed_size UInt64, have_statistics Bool, statistics Tuple(num_values Nullable(UInt64), null_count Nullable(UInt64), distinct_count Nullable(UInt64), min Nullable(String), max Nullable(String))))))
+num_columns     UInt64
+num_rows        UInt64
+num_row_groups  UInt64
+format_version  String
+metadata_size   UInt64
+total_uncompressed_size UInt64
+total_compressed_size   UInt64
+columns Array(Tuple(name String, path String, max_definition_level UInt64, max_repetition_level UInt64, physical_type String, logical_type String, compression String, total_uncompressed_size UInt64, total_compressed_size UInt64, space_saved String, encodings Array(String)))
+row_groups      Array(Tuple(num_columns UInt64, num_rows UInt64, total_uncompressed_size UInt64, total_compressed_size UInt64, columns Array(Tuple(name String, path String, total_compressed_size UInt64, total_uncompressed_size UInt64, have_statistics Bool, statistics Tuple(num_values Nullable(UInt64), null_count Nullable(UInt64), distinct_count Nullable(UInt64), min Nullable(String), max Nullable(String))))))
 ```
 
 Let's have now have a look at the metadata for this file.

docs/cloud/bestpractices/avoidmutations.md

@@ -5,7 +5,7 @@ title: 'Avoid Mutations'
 description: 'Page describing why you should avoid mutations, ALTER queries that manipulate table data through deletion or updates'
 ---
 
-Mutations refers to [ALTER](/sql-reference/statements/alter/) queries that manipulate table data through deletion or updates. Most notably they are queries like ALTER TABLE … DELETE, UPDATE, etc. Performing such queries will produce new mutated versions of the data parts. This means that such statements would trigger a rewrite of whole data parts for all data that was inserted before the mutation, translating to a large amount of write requests.
+Mutations refers to [ALTER](/sql-reference/statements/alter/) queries that manipulate table data through deletion or updates. Most notably they are queries like ALTER TABLE ... DELETE, UPDATE, etc. Performing such queries will produce new mutated versions of the data parts. This means that such statements would trigger a rewrite of whole data parts for all data that was inserted before the mutation, translating to a large amount of write requests.
 
 For updates, you can avoid these large amounts of write requests by using specialised table engines like [ReplacingMergeTree](/engines/table-engines/mergetree-family/replacingmergetree.md) or [CollapsingMergeTree](/engines/table-engines/mergetree-family/collapsingmergetree.md) instead of the default MergeTree table engine.
 

docs/cloud/get-started/cloud-quick-start.md

@@ -273,10 +273,10 @@ In the above query, the output is returned as tab-separated:
 ```response
 Query id: 3604df1c-acfd-4117-9c56-f86c69721121
 
-102 Insert a lot of rows per batch	2022-03-21 00:00:00	1.41421
-102 Sort your data based on your commonly-used queries	2022-03-22 00:00:00	2.718
-101 Hello, ClickHouse!	2022-03-22 14:04:09	-1
-101 Granules are the smallest chunks of data read	2022-03-22 14:04:14	3.14159
+102 Insert a lot of rows per batch      2022-03-21 00:00:00     1.41421
+102 Sort your data based on your commonly-used queries  2022-03-22 00:00:00     2.718
+101 Hello, ClickHouse!  2022-03-22 14:04:09     -1
+101 Granules are the smallest chunks of data read       2022-03-22 14:04:14     3.14159
 
 4 rows in set. Elapsed: 0.005 sec.
 ```

docs/cloud/reference/changelog.md

@@ -1014,7 +1014,7 @@ This release brings an API for retrieving cloud endpoints, an advanced scaling c
   - Fixed server-side parameter binding of the NULL value for Nullable types
 
 ### Bug fixes {#bug-fixes-1}
-* Fixed behavior where running `INSERT INTO … SELECT …` from the SQL console incorrectly applied the same row limit as select queries
+* Fixed behavior where running `INSERT INTO ... SELECT ...` from the SQL console incorrectly applied the same row limit as select queries
 
 
 ## March 23, 2023 {#march-23-2023}

docs/cloud/reference/cloud-compatibility.md

@@ -26,7 +26,7 @@ ClickHouse Cloud provides access to a curated set of capabilities in the open so
 ### DDL syntax {#ddl-syntax}
 For the most part, the DDL syntax of ClickHouse Cloud should match what is available in self-managed installs. A few notable exceptions:
   - Support for `CREATE AS SELECT`, which is currently not available. As a workaround, we suggest using `CREATE ... EMPTY ... AS SELECT` and then inserting into that table (see [this blog](https://clickhouse.com/blog/getting-data-into-clickhouse-part-1) for an example).
-  - Some experimental syntax may be disabled, for instance, `ALTER TABLE … MODIFY QUERY` statement.
+  - Some experimental syntax may be disabled, for instance, `ALTER TABLE ... MODIFY QUERY` statement.
   - Some introspection functionality may be disabled for security purposes, for example, the `addressToLine` SQL function.
   - Do not use `ON CLUSTER` parameters in ClickHouse Cloud - these are not needed. While these are mostly no-op functions, they can still cause an error if you are trying to use [macros](/operations/server-configuration-parameters/settings#macros). Macros often do not work and are not needed in ClickHouse Cloud.
 

docs/cloud/security/azure-privatelink.md

@@ -283,11 +283,11 @@ You need to point "DNS name", taken from [Obtain Azure connection alias for Priv
 
 ```bash
 nslookup xxxxxxxxxx.westus3.privatelink.azure.clickhouse.cloud.
-Server:		127.0.0.53
-Address:	127.0.0.53#53
+Server: 127.0.0.53
+Address: 127.0.0.53#53
 
 Non-authoritative answer:
-Name:	xxxxxxxxxx.westus3.privatelink.azure.clickhouse.cloud
+Name: xxxxxxxxxx.westus3.privatelink.azure.clickhouse.cloud
 Address: 10.0.0.4
 ```
 
@@ -480,7 +480,7 @@ You should receive the following response:
 
 ```response
 Non-authoritative answer:
-Name:	<dns name>
+Name: <dns name>
 Address: 10.0.0.4
 ```
 

docs/concepts/olap.md

@@ -10,12 +10,14 @@ slug: /concepts/olap
 
 [OLAP](https://en.wikipedia.org/wiki/Online_analytical_processing) stands for Online Analytical Processing. It is a broad term that can be looked at from two perspectives: technical and business. At the highest level, you can just read these words backward:
 
+
 **Processing** some source data is processed…
 
 **Analytical** …to produce some analytical reports and insights…
 
 **Online** …in real-time.
 
+
 ## OLAP from the Business Perspective {#olap-from-the-business-perspective}
 
 In recent years business people started to realize the value of data. Companies who make their decisions blindly more often than not fail to keep up with the competition. The data-driven approach of successful companies forces them to collect all data that might be even remotely useful for making business decisions, and imposes on them a need for mechanisms which allow them to analyze this data in a timely manner. Here’s where OLAP database management systems (DBMS) come in.

docs/concepts/why-clickhouse-is-so-fast.md

@@ -103,7 +103,7 @@ If a single node becomes too small to hold the table data, further nodes can be
 
 <iframe width="1024" height="576" src="https://www.youtube.com/embed/dccGLSuYWy0?si=rQ-Jp-z5Ik_-Rb8S" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
 
-> **"ClickHouse is a freak system - you guys have 20 versions of a hash table. You guys have all these amazing things where most systems will have one hash table** **…** **ClickHouse has this amazing performance because it has all these specialized components"** [Andy Pavlo, Database Professor at CMU](https://www.youtube.com/watch?v=Vy2t_wZx4Is&t=3579s)
+> **"ClickHouse is a freak system - you guys have 20 versions of a hash table. You guys have all these amazing things where most systems will have one hash table** **...** **ClickHouse has this amazing performance because it has all these specialized components"** [Andy Pavlo, Database Professor at CMU](https://www.youtube.com/watch?v=Vy2t_wZx4Is&t=3579s)
 
 What sets ClickHouse [apart](https://www.youtube.com/watch?v=CAS2otEoerM) is its meticulous attention to low-level optimization. Building a database that simply works is one thing, but engineering it to deliver speed across diverse query types, data structures, distributions, and index configurations is where the "[freak system](https://youtu.be/Vy2t_wZx4Is?si=K7MyzsBBxgmGcuGU&t=3579)" artistry shines.