fix links

Author: gingerwizard

docs/en/integrations/data-ingestion/clickpipes/index.md

@@ -18,7 +18,7 @@ import PostgresSVG from "../../images/logos/postgresql.svg";
 
 ## Introduction
 
-[ClickPipes](https://clickhouse.com/cloud/clickpipes) is a managed integration platform that makes ingesting data from a diverse set of sources as simple as clicking a few buttons. Designed for the most demanding workloads, ClickPipes's robust and scalable architecture ensures consistent performance and reliability. ClickPipes can be used for long-term streaming needs or one-time data loading job.
+[ClickPipes](/docs/en/integrations/clickpipes) is a managed integration platform that makes ingesting data from a diverse set of sources as simple as clicking a few buttons. Designed for the most demanding workloads, ClickPipes's robust and scalable architecture ensures consistent performance and reliability. ClickPipes can be used for long-term streaming needs or one-time data loading job.
 
 ![ClickPipes stack](./images/clickpipes_stack.png)
 
@@ -64,7 +64,7 @@ Steps:
 ![Assign a custom role](./images/cp_custom_role.png)
 
 ## Error reporting
-ClickPipes will create a table next to your destination table with the postfix `<destination_table_name>_clickpipes_error`. This table will contain any errors from the operations of your ClickPipe (network, connectivity, etc.) and also any data that don't conform to the schema. The error table has a [TTL](https://clickhouse.com/docs/en/engines/table-engines/mergetree-family/mergetree#table_engine-mergetree-ttl) of 7 days.
+ClickPipes will create a table next to your destination table with the postfix `<destination_table_name>_clickpipes_error`. This table will contain any errors from the operations of your ClickPipe (network, connectivity, etc.) and also any data that don't conform to the schema. The error table has a [TTL](/docs/en/engines/table-engines/mergetree-family/mergetree#table_engine-mergetree-ttl) of 7 days.
 If ClickPipes cannot connect to a data source or destination after 15min., ClickPipes instance stops and  stores an appropriate message in the error table (providing the ClickHouse instance is available).
 
 ## F.A.Q
@@ -74,7 +74,7 @@ If ClickPipes cannot connect to a data source or destination after 15min., Click
 
 - **Does ClickPipes support data transformation?**
 
-  Yes, ClickPipes supports basic data transformation by exposing the DDL creation. You can then apply more advanced transformations to the data as it is loaded into its destination table in a ClickHouse Cloud service leveraging ClickHouse's [materialized views feature](https://clickhouse.com/docs/en/guides/developer/cascading-materialized-views).
+  Yes, ClickPipes supports basic data transformation by exposing the DDL creation. You can then apply more advanced transformations to the data as it is loaded into its destination table in a ClickHouse Cloud service leveraging ClickHouse's [materialized views feature](/docs/en/guides/developer/cascading-materialized-views).
 
 - **Does using ClickPipes incur an additional cost?**
 

docs/en/integrations/data-ingestion/data-formats/csv-tsv.md

@@ -40,7 +40,7 @@ FROM INFILE 'data_small.csv'
 FORMAT CSV
 ```
 
-Here, we use the `FORMAT CSV` clause so ClickHouse understands the file format. We can also load data directly from URLs using [url()](/docs/en/sql-reference/table-functions/url.md/) function or from S3 files using [s3()](/docs/en/sql-reference/table-functions/s3.md/) function.
+Here, we use the `FORMAT CSV` clause so ClickHouse understands the file format. We can also load data directly from URLs using [url()](/docs/en/sql-reference/table-functions/url.md) function or from S3 files using [s3()](/docs/en/sql-reference/table-functions/s3.md) function.
 
 :::tip
 We can skip explicit format setting for `file()` and `INFILE`/`OUTFILE`.

docs/en/integrations/data-ingestion/data-formats/json/formats.md

@@ -273,7 +273,7 @@ Note that `JSONAsString` works perfectly fine in cases we have JSON object-per-l
 
 ## Schema for nested objects
 
-In cases when we're dealing with [nested JSON objects](../assets/list-nested.json), we can additionally define schema and use complex types ([`Array`](/docs/en/sql-reference/data-types/array.md/), [`Object Data Type`](/en/sql-reference/data-types/object-data-type) or [`Tuple`](/docs/en/sql-reference/data-types/tuple.md/)) to load data:
+In cases when we're dealing with [nested JSON objects](../assets/list-nested.json), we can additionally define schema and use complex types ([`Array`](/docs/en/sql-reference/data-types/array.md), [`Object Data Type`](/en/sql-reference/data-types/object-data-type) or [`Tuple`](/docs/en/sql-reference/data-types/tuple.md)) to load data:
 
 ```sql
 SELECT *

docs/en/integrations/data-ingestion/data-formats/json/schema.md

@@ -7,7 +7,7 @@ keywords: [json, clickhouse, inserting, loading, formats, schema]
 
 # Designing your schema
 
-While [schema inference](/docs/en/integrations/data-formats/JSON/inference) can be used to establish an initial schema for JSON data and query JSON data files in place, e.g., in S3, users should aim to establish an optimized versioned schema for their data. We discuss the options for modeling JSON structures below.
+While [schema inference](/docs/en/integrations/data-formats/json/inference) can be used to establish an initial schema for JSON data and query JSON data files in place, e.g., in S3, users should aim to establish an optimized versioned schema for their data. We discuss the options for modeling JSON structures below.
 
 ## Extract where possible
 

docs/en/integrations/data-ingestion/data-formats/templates-regex.md

@@ -126,7 +126,7 @@ FORMAT Template SETTINGS format_template_resultset = 'output.results',
 ```
 
 ### Exporting to HTML files
-Template-based results can also be exported to files using an [`INTO OUTFILE`](/docs/en/sql-reference/statements/select/into-outfile.md/) clause. Let's generate HTML files based on given [resultset](assets/html.results) and [row](assets/html.row) formats:
+Template-based results can also be exported to files using an [`INTO OUTFILE`](/docs/en/sql-reference/statements/select/into-outfile.md) clause. Let's generate HTML files based on given [resultset](assets/html.results) and [row](assets/html.row) formats:
 
 ```sql
 SELECT

docs/en/integrations/data-ingestion/dbms/postgresql/data-type-mappings.md

@@ -39,4 +39,4 @@ The following table shows the equivalent ClickHouse data types for Postgres.
 | JSON* | [String](/en/sql-reference/data-types/string), [Variant](/en/sql-reference/data-types/variant), [Nested](/en/sql-reference/data-types/nested-data-structures/nested#nestedname1-type1-name2-type2-), [Tuple](/en/sql-reference/data-types/tuple) |
 | JSONB | [String](/en/sql-reference/data-types/string) |
 
-*\* Production support for JSON in ClickHouse is under development. Currently users can either map JSON as String, and use [JSON functions](/en/sql-reference/functions/json-functions), or map the JSON directly to [Tuples](/en/sql-reference/data-types/tuple) and [Nested](/en/sql-reference/data-types/nested-data-structures/nested) if the structure is predictable. Read more about JSON [here](/en/integrations/data-formats/json#handle-as-structured-data).*
+*\* Production support for JSON in ClickHouse is under development. Currently users can either map JSON as String, and use [JSON functions](/en/sql-reference/functions/json-functions), or map the JSON directly to [Tuples](/en/sql-reference/data-types/tuple) and [Nested](/en/sql-reference/data-types/nested-data-structures/nested) if the structure is predictable. Read more about JSON [here](/en/integrations/data-formats/json/overview).*

docs/en/integrations/language-clients/java/client-v1.md

@@ -214,7 +214,7 @@ ClickHouseClient client = ClickHouseClient.builder()
    .build();
 ```
 
-See the [compression documentation](/en/native-protocol/compression) to learn more about different compression options.
+See the [compression documentation](/docs/en/data-compression/compression-modes) to learn more about different compression options.
 
 ### Multiple queries
 

docs/en/integrations/migration/rockset.md

@@ -47,7 +47,7 @@ Rockset and ClickHouse both support loading data from a variety of sources.
 In Rockset, you create a data source and then create a _collection_ based on that data source.
 There are fully managed integrations for event streaming platforms, OLTP databases, and cloud bucket storage.
 
-In ClickHouse Cloud, the equivalent of fully managed integrations is [ClickPipes](/en/integrations/ClickPipes).
+In ClickHouse Cloud, the equivalent of fully managed integrations is [ClickPipes](/docs/en/integrations/clickpipes).
 ClickPipes supports continuously loading data from event streaming platforms and cloud bucket storage.
 ClickPipes loads data into _tables_.
 
@@ -102,7 +102,7 @@ There are multiple ways to work with JSON in ClickHouse:
 * JSON extract at query time
 * JSON extract at insert time
 
-To understand the best approach for your user case, see [our JSON documentation](/docs/en/integrations/data-formats/json).
+To understand the best approach for your user case, see [our JSON documentation](/docs/en/integrations/data-formats/json/overview).
 
 In addition, ClickHouse will soon have [a Semistructured column data type](https://github.com/ClickHouse/ClickHouse/issues/54864).
 This new type should give users the flexibility Rockset's JSON type offers.