Starrocks

Latest version: v1.2.0

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2.1.10

Release date: June 24, 2022

Bug Fixes
The following bugs are fixed:
- Switching Leader FE node repetitively may cause all load jobs hang and fail. [7350](https://github.com/StarRocks/starrocks/issues/7350)
- Field of DECIMAL(18,2) type is shown as DECIMAL64(18,2) when checking the table schema with DESC SQL. [7309](https://github.com/StarRocks/starrocks/pull/7309)
- BE crashes when the memory usage estimation of MemTable exceeds 4GB, because, during a data skew in load, some fields may occupy a large amount of memory resources. [7161](https://github.com/StarRocks/starrocks/issues/7161)
- A large number of small segment files are created due to the overflow in the calculation of the max_rows_per_segment when there are many input rows in a compaction. [5610](https://github.com/StarRocks/starrocks/issues/5610)


**Full Changelog**: https://github.com/StarRocks/starrocks/compare/2.1.8...2.1.10


Thanks to
Seaven, chaoyli, decster, gengjun-git, mergify, mofeiatwork, satanson, sduzh, trueeyu, xiaoyong-z

2.1.8

Release date: June 10, 2022

Improvements
- The concurrency control mechanism used for internal processing workloads such as schema changes is optimized to reduce the pressure on frontend (FE) metadata. As such, load jobs are less likely to pile up and slow down if these load jobs are concurrently run to load a large amount of data. [6560](https://github.com/StarRocks/starrocks/pull/6560) [#6804](https://github.com/StarRocks/starrocks/pull/6804)
- The performance of StarRocks in loading data at a high frequency is improved. [6532](https://github.com/StarRocks/starrocks/pull/6532) [#6533](https://github.com/StarRocks/starrocks/pull/6533)

Bug Fixes
The following bugs are fixed:
- ALTER operation logs do not record all information about LOAD statements. Therefore, after you perform an ALTER operation on a routine load job, the metadata of the job is lost after checkpoints are created. [6936](https://github.com/StarRocks/starrocks/issues/6936)
- A deadlock may occur if you stop a routine load job. [6450](https://github.com/StarRocks/starrocks/issues/6450)
- By default, a backend (BE) uses the default UTC+8 time zone for a load job. If your server uses the UTC time zone, 8 hours are added to the timestamps in the DateTime column of the table that is loaded by using a Spark load job. [6592](https://github.com/StarRocks/starrocks/issues/6592)
- The GET_JSON_STRING function cannot process non-JSON strings. If you extract a JSON value from a JSON object or array, the function returns NULL. The function has been optimized to return an equivalent JSON-formatted STRING value for a JSON object or array. [6426](https://github.com/StarRocks/starrocks/issues/6426)
- If the data volume is large, a schema change may fail due to excessive memory consumption. Optimizations have been made to allow you to specify memory consumption limits at all stages of a schema change. [6705](https://github.com/StarRocks/starrocks/pull/6705)
- If the number of duplicate values in a column of a table that is being compacted exceeds 0x40000000, the compaction is suspended. [6513](https://github.com/StarRocks/starrocks/issues/6513)
- After an FE restarts, it encounters high I/O and abnormally increasing disk usage due to a few issues in BDB JE v7.3.8 and shows no sign of restoring to normal. The FE is restored to normal after it rolls back to BDB JE v7.3.7. [6634](https://github.com/StarRocks/starrocks/issues/6634)

**Full Changelog**: https://github.com/StarRocks/starrocks/compare/2.1.7...2.1.8

Thanks to
Astralidea, Linkerist, RowenWoo, chaoyli, gengjun-git, meegoo, mergify, rickif, stdpain, xiaoyong-z

2.1.7

Release date: May 26, 2022

Improvements
For window functions in which the frame is set to ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW, if the partition involved in a calculation is large, StarRocks caches all data of the partition before it performs the calculation. In this situation, a large number of memory resources are consumed. StarRocks has been optimized not to cache all data of the partition in this situation. [5829](https://github.com/StarRocks/starrocks/issues/5829)

Bug Fixes
The following bugs are fixed:
- When data is loaded into a table that uses the Primary Key model, data processing errors may occur if the creation time of each data version stored in the system does not monotonically increase due to reasons such as backward-moved system time and related unknown bugs. Such data processing errors cause backends (BEs) to stop. [6046](https://github.com/StarRocks/starrocks/issues/6046)
- Some graphical user interface (GUI) tools automatically configure the set_sql_limit variable. As a result, the SQL statement ORDER BY LIMIT is ignored, and consequently an incorrect number of rows are returned for queries. [5966](https://github.com/StarRocks/starrocks/issues/5966)
- If the DROP SCHEMA statement is executed on a database, the database is forcibly deleted and cannot be restored. [6201](https://github.com/StarRocks/starrocks/issues/6201)
- When JSON-formatted data is loaded, BEs stop if the data contains JSON format errors. For example, key-value pairs are not separated by commas (,). [6098](https://github.com/StarRocks/starrocks/issues/6098)
- When a large amount of data is being loaded in a highly concurrent manner, tasks that are run to write data to disks are piled up on BEs. In this situation, the BEs may stop. [3877](https://github.com/StarRocks/starrocks/issues/3877)
- StarRocks estimates the amount of memory that is required before it performs a schema change on a table. If the table contains a large number of STRING fields, the memory estimation result may be inaccurate. In this situation, if the estimated amount of memory that is required exceeds the maximum memory that is allowed for a single schema change operation, schema change operations that are supposed to be properly run encounter errors. [6322](https://github.com/StarRocks/starrocks/issues/6322)
- After a schema change is performed on a table that uses the Primary Key model, a "duplicate key xxx" error may occur when data is loaded into that table. [5878](https://github.com/StarRocks/starrocks/issues/5878)
- If low-cardinality optimization is performed during Shuffle Join operations, partitioning errors may occur. [4890](https://github.com/StarRocks/starrocks/issues/4890)
- If a colocation group (CG) contains a large number of tables and data is frequently loaded into the tables, the CG may not be able to stay in the stable state. In this case, the JOIN statement does not support Colocate Join operations. StarRocks has been optimized to wait for a little longer during data loading. This way, the integrity of the tablet replicas to which data is loaded can be maximized.

**Full Changelog**: https://github.com/StarRocks/starrocks/compare/2.1.6...2.1.7

Thanks to
Astralidea, HangyuanLiu, Linkerist, Youngwb, chaoyli, decster, dirtysalt, gengjun-git, meegoo, rickif, sevev, stdpain, trueeyu, xiaoyong-z

2.1.6

Release date: May 10, 2022

Bug Fixes
The following bugs are fixed:
- When you run queries after you perform multiple DELETE operations, you may obtain incorrect query results if optimization on low-cardinality columns is performed for the queries. [5712](https://github.com/StarRocks/starrocks/issues/5712)
- If tablets are migrated in specific data ingestion phases, data continues to be written to the original disk on which the tablets are stored. As a result, data is lost, and queries cannot be run properly. [5160](https://github.com/StarRocks/starrocks/issues/5160)
- If you covert values between the DECIMAL and STRING data types, the return values may be in an unexpected precision. [5608](https://github.com/StarRocks/starrocks/issues/5608)
- If you multiply a DECIMAL value by a BIGINT value, an arithmetic overflow may occur. A few adjustments and optimizations are made to fix this bug. [4211](https://github.com/StarRocks/starrocks/pull/4211)

Thanks to
ABingHuang, Astralidea, HangyuanLiu, Seaven, ZiheLiu, caneGuy, gengjun-git, mergify, satanson, sevev, silverbullet233, stdpain

2.1.5

Release date: April 27, 2022
BugFix
The following bugs are fixed:
- The calculation result is not correct when decimal multiplication overflows. After the bug is fixed, NULL is returned when decimal multiplication overflows.
- When statistics have a considerable deviation from the actual statistics, the priority of Collocate Join can be lower than Broadcast Join. As a result, the query planner may not choose Colocate Join as the more appropriate Join strategy. [4817](https://github.com/StarRocks/starrocks/pull/4817)
- Query fails because the plan for complex expressions is wrong when there are more than 4 tables to join.
- BEs may stop working under Shuffle Join when the shuffle column is a low-cardinality column. [4890](https://github.com/StarRocks/starrocks/issues/4890)
- BEs may stop working when the SPLIT function uses a NULL parameter. [4092](https://github.com/StarRocks/starrocks/issues/4092)

Thanks to:
ABingHuang, Astralidea, HangyuanLiu, Linkerist, Seaven, Youngwb, adzfolc, chaoyli, decster, gengjun-git, kangkaisen, liuyehcf, meegoo, mergify, miomiocat, mofeiatwork, rickif, satanson, sevev, stdpain, trueeyu, wyb

2.1.4

Release date: April 8, 2022

New Feature
- The `UUID_NUMERIC` function is supported, which returns a LARGEINT value. Compared with `UUID` function, the performance of `UUID_NUMERIC` function can be improved by nearly 2 orders of magnitude.

BugFix
The following bugs are fixed:
- After deleting columns, adding new partitions, and cloning tablets, the columns' unique ids in old and new tablets may not be the same, which may cause BE to stop working because the system uses a shared tablet schema. [4514](https://github.com/StarRocks/starrocks/issues/4514)
- When data is loading to a StarRocks external table, if the configured FE of the target StarRocks cluster is not a Leader, it will cause the FE to stop working. [4573](https://github.com/StarRocks/starrocks/issues/4573)
- The results of `CAST` function are different in StarRocks version 1.19 and 2.1. [4701](https://github.com/StarRocks/starrocks/pull/4701)
- Query results may be incorrect, when a Duplicate Key table performs schema change and creates materialized view at the same time. [4839](https://github.com/StarRocks/starrocks/issues/4839)

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