Databend Dev Blog

[Databend](https://github.com/datafuselabs/databend) aimed to be an open source **elastic** and **reliable** cloud warehouse, it offers blazing fast query and combines elasticity, simplicity, low cost of the cloud, built to make the Data Cloud easy. ## Big changes Below is a list of some major changes that we don't want you to miss. ### Features - **add bloom filter for single column equivalent expression** by [@junli1026](https://github.com/junli1026) ([#3887](https://github.com/datafuselabs/databend/pull/3887)) - **Jwt Auth for http handler** by [@youngsofun](https://github.com/youngsofun) ([#3993](https://github.com/datafuselabs/databend/pull/3993)) ## Improvement - **add partitions_scanned and partitions_total to planner statistics** by [@BohuTANG](https://github.com/BohuTANG). ([#3909](https://github.com/datafuselabs/databend/pull/3909)) - **clean up metasrv code and test** by [@drmingdrmer](https://github.com/drmingdrmer). ([#3925](https://github.com/datafuselabs/databend/pul...

Analyzing OnTime datasets on AWS EC2 and S3 with Databend step by step. Step 1. Deploy environment ​   EC2 size : c5a.4xlarge EC2 region: <your S3 bucket region> local disk 300G, local disk only used for ontime save and databend complie. Os Type: ubuntu 20 x64 Prepare install package: $sudo apt-get install unzip make mysql- client -core -8.0 Step 2. Deploy Databend ​ 2.1 Compile Databend $git clone https://github.com/datafuselabs/databend.git $cd databend $make setup $export PATH=$PATH:~/.cargo/bin $make build-native Finally, the databend-related binary files are at ./target/release/{databend-meta, databend-query} 2.2  Start Databend # Please replace the s3 env config with your own. export STORAGE_TYPE=s3 export S3_STORAGE_BUCKET=<your-s3-bucket> export S3_STORAGE_REGION=<your-s3-region> export S3_STORAGE_ENDPOINT_URL=<your-bucket>.s3.amazonaws.com export S3_STORAGE_ACCESS_KEY_ID=<your-s3-key-id> export S3_STORAGE_SECRET_ACCESS_KEY=<your-s3-ac...

Databend [1]  aimed to be an open source  elastic  and  reliable  cloud warehouse, it offers blazing fast query and combines elasticity, simplicity, low cost of the cloud, built to make the Data Cloud easy. Big changes Below is a list of some major changes that we don't want you to miss. Features • support  [NOT] IN (a, b, c, ...)  InList SQL  by  @Veeupup [2]  ( #3805 [3] ) Improvement • range filter support more multi-column expression scenarios  by  @zhyass [4] . ( #3851 [5] • refine the error code  by  @BohuTANG [6] . ( #3833 [7] ) • lower the memory usage of BlockStreamWriter  by  @dantengsky [8] . ( #3818 [9] ) • manage role storage in metasrv  by  @flaneur2020 [10] . ( #3878 [11] ) Build/Test/CI • introduce databend Dev container  by  @ZhiHanZ [12] . ( #3853 [13] ) • use peotry to manage all python packages  by  @Xuanwo [14] . ( #3902 [15] ) Bug fixes • fix bug that list_...