Merge pull request #212 from ClickHouse/update-html

Run generateResults.sh on repository

README.md

@@ -53,6 +53,7 @@ TLDR: *All Benchmarks Are ~~Bastards~~ Liars*.
 ### How To Add a New Result
 
 To introduce a new system, simply copy-paste one of the directories and edit the files accordingly:
+
 - `benchmark.sh`: this is the main script to run the benchmark on a fresh VM; Ubuntu 22.04 or newer should be used by default, or any other system if specified in the comments. The script may not necessarily run in a fully automated manner - it is recommended always to copy-paste the commands one by one and observe the results. For managed databases, if the setup requires clicking in the UI, write a `README.md` instead.
 - `README.md`: contains comments and observations if needed. For managed databases, it can describe the setup procedure to be used instead of a shell script.
 - `create.sql`: a CREATE TABLE statement. If it's a NoSQL system, another file like `wtf.json` can be presented.
@@ -64,6 +65,12 @@ To introduce a new result for an existing system on different hardware configura
 
 To introduce a new result for an existing system with a different usage scenario, either copy the whole directory and name it differently (e.g. `timescaledb`, `timescaledb-compression`) or add a new file to the `results` directory.
 
+`index.html` can be re-generated using `./generate-results.sh`. This step is called via a GitHub action and optional.
+
+By default, all tests are run on c6a.4xlarge VM in AWS with 500 GB gp2.
+
+Please help us add more systems and run the benchmarks on more types of VMs.
+
 ### Installation And Fine-Tuning
 
 The systems can be installed or used in any reasonable way: from a binary distribution, from a Docker container, from the package manager, or compiled - whatever is more natural and simple or gives better results.
@@ -192,105 +199,6 @@ Now the new benchmark is easy to use and the results for any system can be repro
 
 We also introduced the [Hardware Benchmark](https://benchmark.clickhouse.com/hardware/) for testing servers and VMs.
 
-## Systems Included
-
-- [x] ClickHouse
-- [x] ClickHouse on local Parquet files
-- [x] ClickHouse operating like "Athena" on remote Parquet files
-- [x] ClickHouse on a VFS over HTTPs on CDN
-- [x] MySQL InnoDB
-- [x] MySQL MyISAM
-- [x] MariaDB
-- [x] MariaDB ColumnStore
-- [x] MemSQL/SingleStore
-- [x] PostgreSQL
-- [x] Greenplum
-- [x] TimescaleDB
-- [x] Citus
-- [x] Vertica (without publishing)
-- [x] QuestDB
-- [x] DuckDB
-- [x] DuckDB over local Parquet files
-- [ ] DuckDB operating like "Athena" on remote Parquet files
-- [x] MonetDB
-- [x] mapD/Omnisci/HeavyAI
-- [x] Databend
-- [x] DataFusion
-- [x] ByteHouse
-- [x] Doris/PALO
-- [x] SelectDB
-- [x] Druid
-- [x] Pinot
-- [x] CrateDB
-- [ ] Spark SQL
-- [x] Starrocks
-- [ ] ShitholeDB
-- [ ] Hive
-- [x] Hydra
-- [ ] Impala
-- [ ] Hyper
-- [x] Umbra
-- [x] SQLite
-- [x] Redshift
-- [x] Redshift Serverless
-- [ ] Redshift Spectrum
-- [ ] Presto
-- [ ] Trino
-- [x] Amazon Athena
-- [x] Bigquery (without publishing)
-- [x] Snowflake
-- [ ] Rockset
-- [ ] CockroachDB
-- [ ] CockroachDB Serverless
-- [ ] Databricks
-- [ ] Planetscale (without publishing)
-- [ ] TiDB (TiFlash)
-- [x] Amazon RDS Aurora for MySQL
-- [x] Amazon RDS Aurora for Postgres
-- [ ] InfluxDB
-- [ ] TDEngine
-- [x] MongoDB
-- [ ] Cassandra
-- [ ] ScyllaDB
-- [x] Elasticsearch
-- [ ] Apache Ignite
-- [x] Motherduck
-- [x] Infobright
-- [ ] Actian Vector
-- [ ] Manticore Search
-- [x] Vertica (without publishing)
-- [ ] Azure Synapse
-- [ ] Starburst Galaxy
-- [ ] MS SQL Server with Column Store Index (without publishing)
-- [ ] Dremio (without publishing)
-- [ ] Exasol
-- [ ] LocustDB
-- [ ] EventQL
-- [ ] Apache Drill
-- [ ] Apache Kudu
-- [ ] Apache Kylin
-- [x] S3 select command in AWS
-- [x] Kinetica
-- [ ] YDB
-- [ ] OceanBase
-- [ ] Boilingdata
-- [x] Byteconity
-- [ ] DolphinDB
-- [x] Oxla
-- [ ] Quickwit
-- [x] AlloyDB
-- [x] ParadeDB
-- [x] GlareDB
-- [ ] Seafowl
-- [ ] Sneller
-- [x] Tablespace
-- [x] Tembo
-- [x] Cloudberry
-
-By default, all tests are run on c6a.4xlarge VM in AWS with 500 GB gp2.
-
-Please help us add more systems and run the benchmarks on more types of VMs.
-
 ## Similar Projects
 
 Many alternative benchmarks are applicable to OLAP DBMS with their own advantages and disadvantages.