Apache Doris Roadmap 2023
Tags: opensource, database, github, cloud
Published: 2023-02-03 10:49:49

Hey Guys, The Roadmap of 2023 has just arrived in time with clear vision of our release schedule and features in progress. We are open to discuss now and you can comment on GitHub. Don't forget to STAR us and we are close to 7k now!

https://github.com/apache/doris/issues/16392

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This is Apache Doris Roadmap 2023.

## Our Main Focus

We plan to optimize Apache Doris for these scenarios:

- **Blazing fast OLAP**
  - Internal reporting 
  - Ad-hoc query 
  - Customer or User facing analytics  (high-concurrency)
- **Blazing fast query engine for datalake and lakehouse** 
  - Query acceleration for Hive 
  - Query acceleration for open table format (Iceberg, Hudi, DeltaLake) 
- **Semi-structured data storage and analysis**
  - Log storage, retrieval, and analysis
  - Time series data storage, retrieval, and analysis
- **High-speed data processing (data engineering)**
  - ETL/ELT acceleration
  - Streaming data warehouse

## Release Schedule

We plan to upgrade Apache Doris at the following pace:

|       | V 1.2.x | V 2.0.x       | V 2.1.x       | V 2.2.x       |
| ----- | ------- | ------------- | ------------- | ------------- |
| Jan.  | 1.2.1   |               |               |               |
| Feb.  | 1.2.2   | 2.0.0 preview |               |               |
| Mar.  | 1.2.3   | 2.0.0         |               |               |
| Apr.  | 1.2.4   | 2.0.1         |               |               |
| May   | 1.2.5   | 2.0.2         | 2.1.0 preview |               |
| Jun.  |         | 2.0.3         | 2.1.0         |               |
| Jul.  |         | 2.0.4         | 2.1.1         |               |
| Aug.  |         | 2.0.5         | 2.1.2         | 2.2.0 preview |
| Sept. |         |               | 2.1.3         | 2.2.0         |
| Oct.  |         |               | 2.1.4         | 2.2.1         |
| Nov.  |         |               | 2.1.5         | 2.2.2         |
| Dec.  |         |               |               | 2.2.3         |

## Features

We plan to develop or continuously optimize these features:

### Hybrid Workloads

- Query excution engine

  - [ ] Pipeline task parallelism

  - [ ] CodeGen

  - [ ] Adaptive execution enhencment

- Spill To Disk

  - [x] Sort Node

  - [ ] HashJoin Node

  - [ ] Aggregation Node

  - [ ] Sort Merge Join

  - [ ] Sort Aggregation

  - [ ] Optimize Spill To disk like compression, encryption, spill disk managment

  - [ ] New query management framework by using Spill To Disk

- Workload manager for hybrid workloads

  - [ ] Resource isolation based on pipeline engine （CPU, Memory, IO）

  - [ ] Resource queue

  - [ ] Async excution

  - [ ] Query priority 

  - [ ] Query scheduler 

### Semi-Structure Data Analysis

- Complex Data Type

  - [x] Array data type & functions 

  - [x] Jsonb data type & functions 

  - [ ] Map data type & functions

  - [ ] Struct data type & functions

  - [ ] IPv4 & IPv6 data type & functions

  - [ ] GEO data type & functions

- Index Enchencment

  - [x] Ngram bloomfilter index

  - [x] Full-Text index for string/number/date

  - [x] BKD numeric index for string/number/date

  - [x] Full-Text & BKD index for Array

  - [ ] Full-Text & BKD index for Map

  - [ ] Full-Text & BKD index for Struct

  - [ ] BKD index for IPv4 & IPv6

  - [ ] BKD index for GEO

- Dynamic Schema Table

  - [x] Dynamic Schema Table syntax

  - [x] Dynamic Schema Table write and read

  - [x] Dynamic Schema Table index

### Lakehouse & Data Integration

- Query acceleration for datalake and lakehouse

  - [x] Parquet, csv, orcfile

  - [x] Iceberg

  - [x] Hudi MOW

  - [ ] Hudi MOR

  - [ ] DeltaLake

  - [ ] Flink Table Store

- Catalog & Cloud Storage integration

  - [x] Hive Meta Store 

  - [x] AWS Glue

  - [x] Alibaba Cloud DLF

  - [x] Object Storage of AWS , Azure,  GCP,  Alibaba Cloud, Tencent Cloud, Huawei Cloud 

- Managed lake engine

  - [ ] Parquet writer

  - [ ] ORC writer

  - [ ] Doris Catalog for Iceberg

  - [ ] Managed Iceberg lake engine

- Data Security

  - [x] Keberos 

  - [x] KMS

  - [x] Apache Ranger integration

  - [ ] Public Cloud (Alibaba Cloud, AWS) IAM Role

- New Spark/Flink Load

  - Writing Doris data format file externally.
  - Refractor the framework of Spark/Flink Load to support batch load.

- Hive/Presto/Spark function compatibility

- Graph database federated query support

### New Optimizer （Nereids）

- Features

  - [x] Fully feature support or replace the old query optimizer

  - [ ] DML （insert,  update, merge）

  - [ ] Query cache

- Performance

  - [x] Optimize the time consumption of the plan stage

  - [ ] RBO Rules enhancement

  - [ ] CBO Rules enhancement, inline CTE, etc.

- Support for hybrid workloads

  - [ ] Optimize rules for datalake engine

  - [ ] Adaptive query plan

  - [ ] Adaptive sort/agg algorithm

- Statistics enhancement

  - [ ] Statistics derivation optimization, improve accuracy, support complex expressions

  - [ ] Richer statistics to support non-uniform distribution data

  - [ ] Optimize statistics persistence and caching mechanism

  - [ ] Auto collect statistics

  - [ ] Optimiza cost model that is more adaptable to distributed scenarios

### Cost Efficiency & Performance

- Cloud Native 

  - [x] Cold & Hot Data Separation

  - [x] Elastic Compute Node

- Low-latency, high-concurrency point query

- Aggregating index & projection

- Performance Self Tunning

- Multi-Table Materialized View

  - [ ] Automatic Incremental refresh

  - [ ] Automatic query rewriting

### Data Modeling & Storage Engine

- Cross Cluster Replication (CCR) & Binlog

  - [ ] CCR to enable higher HA

  - [ ] Binlog to enable streaming computing

- Unique Key Constraint

  - [x] Merge-on-Write (MoW) Unique Key Table

  - [ ] Partial Column Update on MoW UNIQUE Key Table

- DDL Simplification

  - [x] Support functions in partitioning

  - [x] Auto Bucket Number

- Unified Data Model

- General Delete, Update, Merge Support

- Light Schema Change

  - [ ] Do not effect on historical data and work on newer data

### Ecosystem

- Enhance BI tools compatibility
  - Matebase
  - Superset
  - Tableau
- Enhance doris-dbt 
- Enhance Doris-Airbyte
- Enhance integration with cloud data integration tools

### Utility & Stability

- RBAC (Roll-Based-Access-Control) enhancement
- Profiling / Tracing enhancement
- Doris Manager enhancement
- Multi-language UDF
- More Fuzzy tests
- All HTTP APIs support HTTPS and authorization
- Full support for K8s deployment


# Apache Doris
Apache Doris is a real-time analytical database based on MPP architecture, known for its high performance and ease of use. It supports both high-concurrency point queries and high-throughput complex analysis. (https://github.com/apache/doris)

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