On April 11, the DataEase open source data visualization analysis platform officially released the v1.9.0 version. In this version, the DataEase platform has added support for Apache Impala data sources; in terms of dashboards, users can directly set the specified views on the dashboard page, adding web components and streaming media components; in terms of views, Added support for advanced options, some views have added support for threshold-related settings; in terms of X-Pack enhancements, row permissions support built-in system variables, which can more easily control data permissions. In addition, we have also optimized and fixed some other commonly used functions.
new features
■ Added Apache Impala data source support
Impala is an open source project under Apache. It provides SQL semantics and can query petabyte-scale big data stored in Hadoop's HDFS and HBase. Although the existing Hive system also provides SQL semantics, because the underlying execution of Hive uses the MapReduce engine, it is still a batch process, and it is difficult to meet the interactivity of the query. In contrast, the biggest feature and selling point of Impala is its fast responsiveness.
In the v1.9.0 version, DataEase adds Apache Impala data source. Users can add Impala-related connection information to the DataEase data source to display and analyze Impala data in DataEase.
■ View component adds threshold related functions
Generally, the data can be compared with a specific threshold during data analysis, and the state of the data can be clearly and accurately reflected through the comparison of the data. In the DataEase v1.9.0 version, we have added advanced setting functions to some view types, including the auxiliary line settings for line charts and bar charts, and the support for setting the threshold interval settings for dashboards.
■ Support a variety of installation and operation modes
Before the v1.9.0 version, DataEase standard installation will deploy and run five components: DataEase, MySQL, Kettle, Apache Doris FE, and Apache Doris BE by default. For some users, the amount of data they need to analyze and display is not too large, and the Kettle and Apache Doris components are not so necessary in this scenario; for some users with a particularly large amount of data, the standard installation Kettle and Apache Doris, which run in container mode, cannot fully provide the data processing performance required by users.
Starting from the v1.9.0 version, DataEase provides three installation and operation modes, namely thin mode, local mode and cluster mode.
The default installation operation mode is the simplified mode, that is, only the two components of DataEase and MySQL are started, but it can still provide API data source and Excel data set support; the local mode is the default installation method before v1.9.0, including DataEase , MySQL, Kettle, Apache Doris FE, Apache Doris BE five components; cluster mode supports users to add multiple Kettle nodes and Apache Doris cluster settings to meet users' needs for processing performance.
■ Row permission supports built-in system variables (in X-Pack enhancement package)
The data of enterprise users will often contain relevant information such as the department of the enterprise, the role of the user, and the mailbox. In the v1.9.0 version, DataEase has built-in support for some common system variables, such as user ID, user name, user mailbox, user source, user role, organization, etc. Data set administrators can flexibly use these built-in system variables in row permissions, enabling different users to access their own data resources easily and quickly.
In addition to the new features mentioned above, DataEase v1.9.0 also includes many other functional updates and optimizations. Welcome to our official documentation and the Release page of the GitHub repository to view more detailed update logs.
Function optimization
■ refactor (dashboard): The dashboard created by the dashboard template supports the migration of styles and template data;
■ refactor (dashboard): a dashboard with a mobile layout adds a distinguishing mark to the list;
■ style (mobile terminal): mobile terminal dashboard adaptive screen;
■ refactor (X-Pack): associated data set permission verification;
■ refactor: record the position of the dividing line on each page, and do not reset after refreshing (#1390);
■ perf: When optimization starts, the dataset is initialized;
■ refactor: clean up unused views of the official dashboard;
■ refactor: The cache is compatible with Redis stand-alone, sentinel and sharded cluster modes;
■ refactor: encrypt user IDs in public links (#1944);
■ refactor: Increase the strength of the public link password (previously it was a 4-digit random number, now it is a random string consisting of 4-digit uppercase and lowercase letters and numbers).
Bug fixes
■ fix: fix the problem that data cannot be appended after adding fields in Excel data set;
■ fix: fix the problem that the numerical order of the list will appear in text order (#1937);
■ fix: Improve the OIDC login logic (1. OIDC users cannot use the default password to log in in a normal way; 2. OIDC users will not receive a password change prompt after logging in) (#1939);
■ fix: fix the problem of wrong permission to view and share dashboard report on mobile terminal (#1891, #1935);
■ fix: Upgrade the MySQL driver with security holes from 8.0.16 to 8.0.28;
■ fix: fix the issue of incremental synchronization of API datasets;
■ fix: fix the problem that the associated dataset does not support the API dataset;
■ fix: fix the problem that the filter condition is invalid after tab switching;
■ fix: fix the issue of border style after dashboard export to PDF (#1985);
■ fix: fix the problem that other components can also see the picture after setting the background of the component (#1986).