Merge branch 'main' into docs/taostools_main

.gitignore

@@ -99,6 +99,7 @@ tests/examples/JDBC/JDBCDemo/.classpath
 tests/examples/JDBC/JDBCDemo/.project
 tests/examples/JDBC/JDBCDemo/.settings/
 source/libs/parser/inc/sql.*
+source/os/src/timezone/
 tests/script/tmqResult.txt
 tests/system-test/case_to_run.txt
 tests/develop-test/case_to_run.txt
@@ -162,3 +163,12 @@ geos_c.h
 source/libs/parser/src/sql.c
 include/common/ttokenauto.h
 !packaging/smokeTest/pytest_require.txt
+tdengine-test-dir/
+localtime.c
+private.h
+strftime.c
+tzdir.h
+tzfile.h
+coverage.info
+taos
+taosd

Jenkinsfile2

@@ -402,6 +402,7 @@ pipeline {
         WKDIR = '/var/lib/jenkins/workspace'
         WK = '/var/lib/jenkins/workspace/TDinternal'
         WKC = '/var/lib/jenkins/workspace/TDinternal/community'
+        WKPY = '/var/lib/jenkins/workspace/taos-connector-python'
         DOC_WKC = '/root/doc_ci_work'
         td_repo = 'TDengine'
         zh_doc_repo = 'docs.taosdata.com'

cmake/cmake.define

@@ -97,10 +97,13 @@ ELSE()
     SET(TD_TAOS_TOOLS TRUE)
 ENDIF()
 
+SET(TAOS_LIB taos)
+SET(TAOS_LIB_STATIC taos_static)
+
 IF(${TD_WINDOWS})
-    SET(TAOS_LIB taos_static)
+    SET(TAOS_LIB_PLATFORM_SPEC taos_static)
 ELSE()
-    SET(TAOS_LIB taos)
+    SET(TAOS_LIB_PLATFORM_SPEC taos)
 ENDIF()
 
 # build TSZ by default
@@ -128,7 +131,7 @@ IF(TD_WINDOWS)
         SET(COMMON_FLAGS "/w /D_WIN32 /DWIN32 /Zi /MTd")
     ENDIF()
 
-    SET(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} /MANIFEST:NO")
+    SET(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} /MANIFEST:NO /FORCE:MULTIPLE")
 
     # IF (MSVC AND (MSVC_VERSION GREATER_EQUAL 1900))
     # SET(COMMON_FLAGS "${COMMON_FLAGS} /Wv:18")

cmake/cmake.version

@@ -2,7 +2,7 @@
 IF (DEFINED VERNUMBER)
   SET(TD_VER_NUMBER ${VERNUMBER})
 ELSE ()
-  SET(TD_VER_NUMBER "3.3.4.8.alpha")
+  SET(TD_VER_NUMBER "3.3.5.0.alpha")
 ENDIF ()
 
 IF (DEFINED VERCOMPATIBLE)

cmake/libuv_CMakeLists.txt.in

@@ -2,7 +2,7 @@
 # libuv
 ExternalProject_Add(libuv
         GIT_REPOSITORY https://github.com/libuv/libuv.git
-        GIT_TAG v1.48.0
+        GIT_TAG v1.49.2
         SOURCE_DIR "${TD_CONTRIB_DIR}/libuv"
         BINARY_DIR "${TD_CONTRIB_DIR}/libuv"
         CONFIGURE_COMMAND ""

cmake/tz_CMakeLists.txt.in

@@ -0,0 +1,15 @@
+# timezone
+ExternalProject_Add(tz
+        GIT_REPOSITORY https://github.com/eggert/tz.git
+        GIT_TAG main
+        SOURCE_DIR "${TD_CONTRIB_DIR}/tz"
+        BINARY_DIR ""
+        CONFIGURE_COMMAND ""
+        #BUILD_COMMAND ""
+        INSTALL_COMMAND ""
+        TEST_COMMAND ""
+        GIT_SHALLOW true
+        GIT_PROGRESS true
+        BUILD_COMMAND ""
+)
+

contrib/CMakeLists.txt

@@ -106,6 +106,10 @@ cat("${TD_SUPPORT_DIR}/zlib_CMakeLists.txt.in" ${CONTRIB_TMP_FILE})
 # cJson
 cat("${TD_SUPPORT_DIR}/cjson_CMakeLists.txt.in" ${CONTRIB_TMP_FILE})
 
+if(NOT ${TD_WINDOWS})
+    cat("${TD_SUPPORT_DIR}/tz_CMakeLists.txt.in" ${CONTRIB_TMP_FILE})
+endif(NOT ${TD_WINDOWS})
+
 # xz
 # cat("${TD_SUPPORT_DIR}/xz_CMakeLists.txt.in" ${CONTRIB_TMP_FILE})
 
@@ -651,6 +655,35 @@ if(${TD_LINUX} AND ${BUILD_WITH_S3})
     add_subdirectory(azure-cmake EXCLUDE_FROM_ALL)
 endif()
 
+IF(TD_LINUX)
+    SET(TZ_OUTPUT_PATH /usr/share/zoneinfo)
+ELSEIF(TD_DARWIN)
+    SET(TZ_OUTPUT_PATH /var/db/timezone/zoneinfo)
+ENDIF()
+
+
+if(NOT ${TD_WINDOWS})
+    MESSAGE(STATUS "timezone file path: " ${TZ_OUTPUT_PATH})
+
+    execute_process(
+            COMMAND make TZDIR=${TZ_OUTPUT_PATH}/ clean tzdir.h
+            WORKING_DIRECTORY "${TD_CONTRIB_DIR}/tz"
+    )
+
+    set(TZ_SRC_DIR "${TD_SOURCE_DIR}/source/os/src/timezone")
+    file(REMOVE_RECURSE ${TZ_SRC_DIR})
+    file(MAKE_DIRECTORY ${TZ_SRC_DIR})
+    file(COPY ${TD_CONTRIB_DIR}/tz/private.h ${TD_CONTRIB_DIR}/tz/tzdir.h ${TD_CONTRIB_DIR}/tz/tzfile.h
+            ${TD_CONTRIB_DIR}/tz/localtime.c ${TD_CONTRIB_DIR}/tz/strftime.c
+            DESTINATION ${TZ_SRC_DIR})
+endif(NOT ${TD_WINDOWS})
+
+#if(NOT ${TD_WINDOWS})
+#    execute_process(
+#            COMMAND make CFLAGS+=-fPIC CFLAGS+=-g TZDIR=${TZ_OUTPUT_PATH} clean libtz.a
+#            WORKING_DIRECTORY "${TD_CONTRIB_DIR}/tz"
+#    )
+#endif(NOT ${TD_WINDOWS})
 # ================================================================================================
 # Build test
 # ================================================================================================

contrib/test/CMakeLists.txt

@@ -28,6 +28,9 @@ if(${BUILD_WITH_TRAFT})
     # add_subdirectory(traft)
 endif(${BUILD_WITH_TRAFT})
 
-add_subdirectory(azure)
+if(${BUILD_S3})
+  add_subdirectory(azure)
+endif()
+
 add_subdirectory(tdev)
 add_subdirectory(lz4)

docs/en/06-advanced/05-data-in/07-mqtt.md

@@ -112,14 +112,14 @@ Fill in the example data from the MQTT message body in **Message Body**.
 
 JSON data supports JSONObject or JSONArray, and the json parser can parse the following data:
 
-``` json
+```json
 {"id": 1, "message": "hello-word"}
 {"id": 2, "message": "hello-word"}
 ```
 
 or
 
-``` json
+```json
 [{"id": 1, "message": "hello-word"},{"id": 2, "message": "hello-word"}]
 ```
 

docs/en/06-advanced/05-data-in/08-kafka.md

@@ -109,7 +109,7 @@ In addition, the [Kerberos](https://web.mit.edu/kerberos/) authentication servic
 
 After configuration, you can use the [kcat](https://github.com/edenhill/kcat) tool to verify Kafka topic consumption:
 
-```bash
+```shell
 kcat <topic> \
   -b <kafka-server:port> \
   -G kcat \
@@ -171,14 +171,14 @@ Enter sample data from the Kafka message body in **Message Body**.
 
 JSON data supports JSONObject or JSONArray, and the following data can be parsed using a JSON parser:
 
-``` json
+```json
 {"id": 1, "message": "hello-word"}
 {"id": 2, "message": "hello-word"}
 ```
 
 or
 
-``` json
+```json
 [{"id": 1, "message": "hello-word"},{"id": 2, "message": "hello-word"}]
 ```
 

docs/en/06-advanced/05-data-in/index.md

@@ -83,15 +83,15 @@ Parsing is the process of parsing unstructured strings into structured data. The
 
 JSON parsing supports JSONObject or JSONArray. The following JSON sample data can automatically parse fields: `groupid`, `voltage`, `current`, `ts`, `inuse`, `location`.
 
-``` json
+```json
 {"groupid": 170001, "voltage": "221V", "current": 12.3, "ts": "2023-12-18T22:12:00", "inuse": true, "location": "beijing.chaoyang.datun"}
 {"groupid": 170001, "voltage": "220V", "current": 12.2, "ts": "2023-12-18T22:12:02", "inuse": true, "location": "beijing.chaoyang.datun"}
 {"groupid": 170001, "voltage": "216V", "current": 12.5, "ts": "2023-12-18T22:12:04", "inuse": false, "location": "beijing.chaoyang.datun"}
 ```
 
 Or
 
-``` json
+```json
 [{"groupid": 170001, "voltage": "221V", "current": 12.3, "ts": "2023-12-18T22:12:00", "inuse": true, "location": "beijing.chaoyang.datun"},
 {"groupid": 170001, "voltage": "220V", "current": 12.2, "ts": "2023-12-18T22:12:02", "inuse": true, "location": "beijing.chaoyang.datun"},
 {"groupid": 170001, "voltage": "216V", "current": 12.5, "ts": "2023-12-18T22:12:04", "inuse": false, "location": "beijing.chaoyang.datun"}]
@@ -101,7 +101,7 @@ Subsequent examples will only explain using JSONObject.
 
 The following nested JSON data can automatically parse fields `groupid`, `data_voltage`, `data_current`, `ts`, `inuse`, `location_0_province`, `location_0_city`, `location_0_datun`, and you can also choose which fields to parse and set aliases for the parsed fields.
 
-``` json
+```json
 {"groupid": 170001, "data": { "voltage": "221V", "current": 12.3 }, "ts": "2023-12-18T22:12:00", "inuse": true, "location": [{"province": "beijing", "city":"chaoyang", "street": "datun"}]}
 ```
 
@@ -114,7 +114,7 @@ The following nested JSON data can automatically parse fields `groupid`, `data_v
 
 You can use **named capture groups** in regular expressions to extract multiple fields from any string (text) field. As shown in the figure, extract fields such as access IP, timestamp, and accessed URL from nginx logs.
 
-``` re
+```regex
 (?<ip>\b(?:[0-9]{1,3}\.){3}[0-9]{1,3}\b)\s-\s-\s\[(?<ts>\d{2}/\w{3}/\d{4}:\d{2}:\d{2}:\d{2}\s\+\d{4})\]\s"(?<method>[A-Z]+)\s(?<url>[^\s"]+).*(?<status>\d{3})\s(?<length>\d+)
 ```
 
@@ -133,7 +133,7 @@ Custom rhai syntax scripts for parsing input data (refer to `https://rhai.rs/boo
 
 For example, for data reporting three-phase voltage values, which are entered into three subtables respectively, such data needs to be parsed
 
-``` json
+```json
 {
     "ts": "2024-06-27 18:00:00", 
     "voltage": "220.1,220.3,221.1", 
@@ -164,7 +164,7 @@ The final parsing result is shown below:
 
 The parsed data may still not meet the data requirements of the target table. For example, the original data collected by a smart meter is as follows (in json format):
 
-``` json
+```json
 {"groupid": 170001, "voltage": "221V", "current": 12.3, "ts": "2023-12-18T22:12:00", "inuse": true, "location": "beijing.chaoyang.datun"}
 {"groupid": 170001, "voltage": "220V", "current": 12.2, "ts": "2023-12-18T22:12:02", "inuse": true, "location": "beijing.chaoyang.datun"}
 {"groupid": 170001, "voltage": "216V", "current": 12.5, "ts": "2023-12-18T22:12:04", "inuse": false, "location": "beijing.chaoyang.datun"}

docs/en/07-develop/01-connect.md

@@ -7,19 +7,19 @@ import Tabs from "@theme/Tabs";
 import TabItem from "@theme/TabItem";
 import Image from '@theme/IdealImage';
 import imgConnect from '../assets/connecting-to-tdengine-01.png';
-import ConnJava from "./_connect_java.mdx";
-import ConnGo from "./_connect_go.mdx";
-import ConnRust from "./_connect_rust.mdx";
-import ConnNode from "./_connect_node.mdx";
-import ConnPythonNative from "./_connect_python.mdx";
-import ConnCSNative from "./_connect_cs.mdx";
-import ConnC from "./_connect_c.mdx";
-import InstallOnLinux from "../14-reference/05-connector/_linux_install.mdx";
-import InstallOnWindows from "../14-reference/05-connector/_windows_install.mdx";
-import InstallOnMacOS from "../14-reference/05-connector/_macos_install.mdx";
-import VerifyLinux from "../14-reference/05-connector/_verify_linux.mdx";
-import VerifyMacOS from "../14-reference/05-connector/_verify_macos.mdx";
-import VerifyWindows from "../14-reference/05-connector/_verify_windows.mdx";
+import ConnJava from "../assets/resources/_connect_java.mdx";
+import ConnGo from "../assets/resources/_connect_go.mdx";
+import ConnRust from "../assets/resources/_connect_rust.mdx";
+import ConnNode from "../assets/resources/_connect_node.mdx";
+import ConnPythonNative from "../assets/resources/_connect_python.mdx";
+import ConnCSNative from "../assets/resources/_connect_cs.mdx";
+import ConnC from "../assets/resources/_connect_c.mdx";
+import InstallOnLinux from "../assets/resources/_linux_install.mdx";
+import InstallOnWindows from "../assets/resources/_windows_install.mdx";
+import InstallOnMacOS from "../assets/resources/_macos_install.mdx";
+import VerifyLinux from "../assets/resources/_verify_linux.mdx";
+import VerifyMacOS from "../assets/resources/_verify_macos.mdx";
+import VerifyWindows from "../assets/resources/_verify_windows.mdx";
 
 TDengine provides a rich set of application development interfaces. To facilitate users in quickly developing their applications, TDengine supports connectors for multiple programming languages. The official connectors include support for C/C++, Java, Python, Go, Node.js, C#, Rust, Lua (community contribution), and PHP (community contribution). These connectors support connecting to the TDengine cluster using the native interface (taosc) and REST interface (not supported in some languages yet). Community developers have also contributed several unofficial connectors, such as ADO.NET connector, Lua connector, and PHP connector. Additionally, TDengine can directly call the REST API provided by taosadapter for data writing and querying operations.
 

docs/en/07-develop/02-sql.md

@@ -83,14 +83,14 @@ Next, create a supertable (STABLE) named `meters`, whose table structure include
 
 Create Database
 
-```bash
+```shell
 curl --location -uroot:taosdata 'http://127.0.0.1:6041/rest/sql' \
 --data 'CREATE DATABASE IF NOT EXISTS power'
 ```
 
 Create Table, specify the database as `power` in the URL
 
-```bash
+```shell
 curl --location -uroot:taosdata 'http://127.0.0.1:6041/rest/sql/power' \
 --data 'CREATE STABLE IF NOT EXISTS meters (ts TIMESTAMP, current FLOAT, voltage INT, phase FLOAT) TAGS (groupId INT, location BINARY(24))'
 ```
@@ -167,7 +167,7 @@ NOW is an internal system function, defaulting to the current time of the client
 
 Write data
 
-```bash
+```shell
 curl --location -uroot:taosdata 'http://127.0.0.1:6041/rest/sql' \
 --data 'INSERT INTO power.d1001 USING power.meters TAGS(2,'\''California.SanFrancisco'\'') VALUES (NOW + 1a, 10.30000, 219, 0.31000) (NOW + 2a, 12.60000, 218, 0.33000) (NOW + 3a, 12.30000, 221, 0.31000) power.d1002 USING power.meters TAGS(3, '\''California.SanFrancisco'\'') VALUES (NOW + 1a, 10.30000, 218, 0.25000)'
 ```
@@ -247,7 +247,7 @@ Rust connector also supports using **serde** for deserializing to get structured
 
 Query Data
 
-```bash
+```shell
 curl --location -uroot:taosdata 'http://127.0.0.1:6041/rest/sql' \
 --data 'SELECT ts, current, location FROM power.meters limit 100'
 ```
@@ -329,7 +329,7 @@ Below are code examples of setting reqId to execute SQL in various language conn
 
 Query data, specify reqId as 3
 
-```bash
+```shell
 curl --location -uroot:taosdata 'http://127.0.0.1:6041/rest/sql?req_id=3' \
 --data 'SELECT ts, current, location FROM power.meters limit 1'
 ```

docs/en/07-develop/09-udf.md

@@ -273,19 +273,19 @@ To better operate the above data structures, some convenience functions are prov
 
 Create table:
 
-```bash
+```shell
 create table battery(ts timestamp, vol1 float, vol2 float, vol3 float, deviceId varchar(16));
 ```
 
 Create custom function:
 
-```bash
+```shell
 create aggregate function max_vol as '/root/udf/libmaxvol.so' outputtype binary(64) bufsize 10240 language 'C'; 
 ```
 
 Use custom function:
 
-```bash
+```shell
 select max_vol(vol1, vol2, vol3, deviceid) from battery;
 ```
 
@@ -334,7 +334,7 @@ When developing UDFs in Python, you need to implement the specified interface fu
 
 The interface for scalar functions is as follows.
 
-```Python
+```python
 def process(input: datablock) -> tuple[output_type]:
 ```
 
@@ -347,7 +347,7 @@ The main parameters are as follows:
 
 The interface for aggregate functions is as follows.
 
-```Python
+```python
 def start() -> bytes:
 def reduce(inputs: datablock, buf: bytes) -> bytes
 def finish(buf: bytes) -> output_type:
@@ -365,7 +365,7 @@ Finally, when all row data blocks have been processed, the finish function is ca
 
 The interfaces for initialization and destruction are as follows.
 
-```Python
+```python
 def init()
 def destroy()
 ```
@@ -381,7 +381,7 @@ Parameter description:
 
 The template for developing scalar functions in Python is as follows.
 
-```Python
+```python
 def init():
     # initialization
 def destroy():
@@ -393,7 +393,7 @@ def process(input: datablock) -> tuple[output_type]:
 
 The template for developing aggregate functions in Python is as follows.
 
-```Python
+```python
 def init():
     #initialization
 def destroy():
@@ -828,7 +828,7 @@ Through this example, we learned how to define aggregate functions and print cus
 <details>
 <summary>pybitand.py</summary>
 
-```Python
+```python
 {{#include tests/script/sh/pybitand.py}}
 ```