docs: add newlines

docs/benchmarks/log/README.md

@@ -29,7 +29,7 @@ INSERT INTO test_table (message, timestamp) VALUES ()
 The goal is to test fuzzy search performance for each database. In real scenarios it means the log is produced by some kind of middleware and inserted directly into the database.
 
 ## Creating tables
-See [here](./create_table.sql) for GreptimeDB and Clickhouse's create table clause. 
+See [here](./create_table.sql) for GreptimeDB and Clickhouse's create table clause.
 The mapping of Elastic search is created automatically.
 
 ## Vector Configuration
@@ -41,11 +41,11 @@ Please refer to [SQL query](./query.sql) for GreptimeDB and Clickhouse, and [que
 
 ## Steps to reproduce
 0. Decide whether to run structured model test or unstructured mode test.
-1. Build vector binary(see vector's config file for specific branch) and databases binaries accordingly. 
+1. Build vector binary(see vector's config file for specific branch) and databases binaries accordingly.
 2. Create table in GreptimeDB and Clickhouse in advance.
 3. Run vector to insert data.
 4. When data insertion is finished, run queries against each database. Note: you'll need to update timerange value after data insertion.
 
 ## Addition
 - You can tune GreptimeDB's configuration to get better performance.
-- You can setup GreptimeDB to use S3 as storage, see [here](https://docs.greptime.com/user-guide/operations/configuration/#storage-options).
+- You can setup GreptimeDB to use S3 as storage, see [here](https://docs.greptime.com/user-guide/operations/configuration/#storage-options).

docs/benchmarks/log/create_table.sql

@@ -51,6 +51,6 @@ CREATE TABLE IF NOT EXISTS test_table
     message String,
     timestamp String,
     INDEX inv_idx(message) TYPE full_text(0) GRANULARITY 1
-) 
+)
 ENGINE = MergeTree()
-ORDER BY tuple();
+ORDER BY tuple();

docs/benchmarks/log/query.md

@@ -196,4 +196,4 @@ URL: `http://127.0.0.1:9200/_search`
     }
   }
 }
-```
+```

docs/benchmarks/log/structured_vector.toml

@@ -54,4 +54,4 @@ compression = "none"
 doc_type = "_doc"
 endpoints = [ "http://127.0.0.1:9200" ]
 id_key = "id"
-mode = "bulk"
+mode = "bulk"

docs/benchmarks/log/unstructured_vector.toml

@@ -40,4 +40,4 @@ compression = "none"
 doc_type = "_doc"
 endpoints = [ "http://127.0.0.1:9200" ]
 id_key = "id"
-mode = "bulk"
+mode = "bulk"