Module Module Module Input Tables Computing Task Result Table Pipeline = Directed Acyclic Graph (DAG) of modules Module = Input + Task + Output Task = Query or external program Query = “CREATE behavioral pattern in the time series data • Or even... randomly Example: Finding a shortest path in the graph • Iterating Example: Training a regression model • Handling domain-specific data Example: Computing • By character • By token • Popular among ML algorithm engineers Simdjson • An extremely fast JSON parser based on AVX2 Instruction Set • Structured data extraction (JSONExtract) • We can pass the

· · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 1816 11.10.9 TiCDC Canal-JSON Protocol · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 1828 14 11.10.10Quick 5.1 5.0 4.0 Numeric types Y Y Y Y Y Y Date and time types Y Y Y Y Y Y String types Y Y Y Y Y Y JSON type Experimental Experimental Experimental Experimental Experimental Experimental Control flow functions Y Y Y Y Y Y Encryption and compression functions Y Y Y Y Y Y Information functions Y Y Y Y Y Y JSON functions Experimental Experimental Experimental Experimental Experimental Experimental Aggregation

real time when TiDB clusters are running. You can check the performance analysis result in a flame graph, which is more observ- able and shortens troubleshooting time. This feature is disabled by default 3 5.2 5.1 5.0 4.0 Numeric types Y Y Y Y Y Date and time types Y Y Y Y Y String types Y Y Y Y Y JSON type Experimental Experimental Experimental Experimental Experimental Control flow functions Y Y operators Y Y Y Y Y Encryption and compression functions Y Y Y Y Y Information functions Y Y Y Y Y JSON functions Experimental Experimental Experimental Experimental Experimental Aggregation functions

operators 5.2 5.1 5.0 4.0 Numeric types Y Y Y Y Date and time types Y Y Y Y String types Y Y Y Y JSON type Experimental Experimental Experimental Experimental Control flow functions Y Y Y Y String functions and operators Y Y Y Y Encryption and compression functions Y Y Y Y Information functions Y Y Y Y JSON functions Experimental Experimental Experimental Experimental Aggregation functions Y Y Y Y Window index for details. (Introduced in v4.0) • Generated Columns. • User-Defined Variables. • JSON data type and JSON functions. • Prepare Plan cache. (Introduced in v4.0) • Using ALTER TABLE to modify multiple

* Add the binary MQ format designed for TiDB. It is more compact than the open protocols based on JSON #1621 * Remove support for file sorter #2114 * Support log rotation configurations #2182 – TiDB CREATE �→ TABLE #311 39 2.2.4 Improvements • TiDB – Support pushing down the built-in function json_unquote() to TiKV #24415 – Support removing the union branch from the dual table #25614 – Optimize the wrong tikv_raftstore_hibernated_peer_state metric #10330 – Fix the wrong arguments type of the json_unquote() function in the coprocessor #10176 – Skip clearing callback during graceful shutdown to

TiKV �→ enables remote processing of heap profiles. You can now directly �→ access the flame graph and call graph of heap profile. This feature 38 �→ provides the same simple and easy-to-use experience 0, TiKV enables remote processing of heap profiles. You can now directly access the flame graph and call graph of heap profile. This feature provides the same simple and easy-to-use experience as Go heap types Y Y Y Y Y Y Y Y Y Y Date and time types Y Y Y Y Y Y Y Y Y Y String types Y Y Y Y Y Y Y Y Y Y JSON type Y Y Y E E E E E E E Control flow functions Y Y Y Y Y Y Y Y Y Y String functions Y Y Y Y Y Y

@v01dstar @tonyxuqqi To better support TiDB wide table write scenarios, especially with support for JSON, starting from TiDB v7.6.0, the Titan engine is enabled by default. The Titan engine automatically down the following JSON functions to TiFlash #48350 #48986 #48994 #49345 #49392 @SeaRise @yibin87 • JSON_UNQUOTE() • JSON_ARRAY() • JSON_DEPTH() • JSON_VALID() • JSON_KEYS() • JSON_CONTAINS_PATH() For to object storage by increasing parallelism #10098 @CharlesCheung96 • Support making TiCDC Canal-JSON content format compatible with the content format of the official Canal output by setting content-compatible

when multiple Regions are concurrently applying snapshots #9329 @CalvinNeo • Fix the issue that some JSON functions unsupported by TiFlash are pushed down to TiFlash #9444 @windtalker • Tools • Backup & Y Y Y Y Y Y Y Date and time types Y Y Y Y Y Y Y Y Y Y Y Y String types Y Y Y Y Y Y Y Y Y Y Y Y JSON type Y Y Y Y Y Y Y E E E E E Vectort types E N N N N N N N N N N N Control flow functions Y Y Y Vector functions and operators E N N N N N N N N N N N Information functions Y Y Y Y Y Y Y Y Y Y Y Y JSON functions Y Y Y Y Y Y Y E E E E E Aggregation functions Y Y Y Y Y Y Y Y Y Y Y Y Window functions

when multiple Regions are concurrently applying snapshots #9329 @CalvinNeo • Fix the issue that some JSON functions unsupported by TiFlash are pushed down to TiFlash #9444 @windtalker • Tools • Backup & Y Y Y Y Y Y Y Date and time types Y Y Y Y Y Y Y Y Y Y Y Y String types Y Y Y Y Y Y Y Y Y Y Y Y JSON type Y Y Y Y Y Y Y E E E E E Vectort types E N N N N N N N N N N N Control flow functions Y Y Y Vector functions and operators E N N N N N N N N N N N Information functions Y Y Y Y Y Y Y Y Y Y Y Y JSON functions Y Y Y Y Y Y Y E E E E E Aggregation functions Y Y Y Y Y Y Y Y Y Y Y Y Window functions

improving SQL execution performance. This is particularly effective for queries containing JSON query functions or JSON value attribute functions. Starting from v8.3.0, TiDB enables the Projection �→ operator OFF to ON. When this feature is enabled, the optimizer automatically pushes eligible JSON query functions and JSON value attribute functions down to the storage engine. For more information, see documentation results during parallel calculation #55290 @xzhangxian1008 • Fix the issue of wrong JSON_TYPE when casting YEAR to JSON format #54494 @YangKeao • Fix the issue that the value range of the tidb_schema_cache_size