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T
TDengine
提交 a29785df 编写于 作者: H Hongze Cheng
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Merge branch '3.0' of https://github.com/taosdata/TDengine into enh/tsdb_optimize

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cmake/taostools_CMakeLists.txt.in
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......@@ -2,7 +2,7 @@
# taos-tools
ExternalProject_Add(taos-tools
GIT_REPOSITORY https://github.com/taosdata/taos-tools.git
GIT_TAG 7651857
GIT_TAG e82b9fc
SOURCE_DIR "${TD_SOURCE_DIR}/tools/taos-tools"
BINARY_DIR ""
#BUILD_IN_SOURCE TRUE
......
docs/en/13-operation/03-tolerance.md
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......@@ -18,14 +18,8 @@ To achieve absolutely no data loss, set wal_level to 2 and wal_fsync_period to 0
## Disaster Recovery
TDengine uses replication to provide high availability.
TDengine provides disaster recovery by using taosX to replicate data between two TDengine clusters which are deployed in two distant data centers. Assume there are two TDengine clusters, A and B, A is the source and B is the target, and A takes the workload of writing and querying. You can deploy `taosX` in the data center where cluster A resides in, `taosX` consumes the data written into cluster A and writes into cluster B. If the data center of cluster A is disrupted because of disaster, you can switch to cluster B to take the workload of data writing and querying, and deploy a `taosX` in the data center of cluster B to replicate data from cluster B to cluster A if cluster A has been recovered, or another cluster C if cluster A has not been recovered.
A TDengine cluster is managed by mnodes. You can configure up to three mnodes to ensure high availability. The data replication between mnode replicas is performed in a synchronous way to guarantee metadata consistency.
You can use the data replication feature of `taosX` to build more complicated disaster recovery solution.
The number of replicas for time series data in TDengine is associated with each database. There can be many databases in a cluster and each database can be configured with a different number of replicas. When creating a database, the parameter `replica` is used to specify the number of replicas. To achieve high availability, set `replica` to 3.
The number of dnodes in a TDengine cluster must NOT be lower than the number of replicas for any database, otherwise it would fail when trying to create a table.
As long as the dnodes of a TDengine cluster are deployed on different physical machines and the replica number is higher than 1, high availability can be achieved without any other assistance. For disaster recovery, dnodes of a TDengine cluster should be deployed in geographically different data centers.
Alternatively, you can use taosX to synchronize the data from one TDengine cluster to another cluster in a remote location. However, taosX is only available in TDengine enterprise version, for more information please contact tdengine.com.
taosX is only provided in TDengine enterprise edition, for more details please contact business@tdengine.com.
docs/en/14-reference/12-config/index.md
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......@@ -99,6 +99,9 @@ The parameters described in this document by the effect that they have on the sy
## Monitoring Parameters
:::note
Please note the `taoskeeper` needs to be installed and running to create the `log` database and receiving metrics sent by `taosd` as the full monitoring solution.
### monitor
| Attribute | Description |
......
docs/en/14-reference/14-taosKeeper.md
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......@@ -13,14 +13,12 @@ taosKeeper is a tool for TDengine that exports monitoring metrics. With taosKeep
## Installation
<!-- There are two ways to install taosKeeper: -->
There are two ways to install taosKeeper:
Methods of installing taosKeeper:
<!--- Installing the official TDengine installer will automatically install taosKeeper. Please refer to [TDengine installation](/operation/pkg-install) for details. -->
- You can compile taosKeeper separately and install it. Please refer to the [taosKeeper](https://github.com/taosdata/taoskeeper) repository for details. -->
You can compile taosKeeper separately and install it. Please refer to the [taosKeeper](https://github.com/taosdata/taoskeeper) repository for details.
- Installing the official TDengine installer will automatically install taosKeeper. Please refer to [TDengine installation](/operation/pkg-install) for details.
- You can compile taosKeeper separately and install it. Please refer to the [taosKeeper](https://github.com/taosdata/taoskeeper) repository for details.
## Configuration and Launch
### Configuration
......@@ -110,7 +108,7 @@ The following `launchctl` commands can help you manage taoskeeper service:
#### Launch With Configuration File
You can quickly launch taosKeeper with the following commands. If you do not specify a configuration file, `/etc/taos/keeper.toml` is used by default. If this file does not specify configurations, the default values are used.
You can quickly launch taosKeeper with the following commands. If you do not specify a configuration file, `/etc/taos/keeper.toml` is used by default. If this file does not specify configurations, the default values are used.
```shell
$ taoskeeper -c <keeper config file>
......@@ -188,19 +186,19 @@ $ curl http://127.0.0.1:6043/metrics
Sample result set (excerpt):
```shell
# HELP taos_cluster_info_connections_total
# HELP taos_cluster_info_connections_total
# TYPE taos_cluster_info_connections_total counter
taos_cluster_info_connections_total{cluster_id="5981392874047724755"} 16
# HELP taos_cluster_info_dbs_total
# HELP taos_cluster_info_dbs_total
# TYPE taos_cluster_info_dbs_total counter
taos_cluster_info_dbs_total{cluster_id="5981392874047724755"} 2
# HELP taos_cluster_info_dnodes_alive
# HELP taos_cluster_info_dnodes_alive
# TYPE taos_cluster_info_dnodes_alive counter
taos_cluster_info_dnodes_alive{cluster_id="5981392874047724755"} 1
# HELP taos_cluster_info_dnodes_total
# HELP taos_cluster_info_dnodes_total
# TYPE taos_cluster_info_dnodes_total counter
taos_cluster_info_dnodes_total{cluster_id="5981392874047724755"} 1
# HELP taos_cluster_info_first_ep
# HELP taos_cluster_info_first_ep
# TYPE taos_cluster_info_first_ep gauge
taos_cluster_info_first_ep{cluster_id="5981392874047724755",value="hlb:6030"} 1
```
\ No newline at end of file
```
docs/zh/14-reference/12-config/index.md
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......@@ -99,6 +99,9 @@ taos --dump-config
## 监控相关
:::note
请注意，完整的监控功能需要安装并运行 `taoskeeper` 服务。taoskeeper 负责接收监控指标数据并创建 `log` 库。
### monitor
| 属性 | 说明 |
......
docs/zh/14-reference/14-taosKeeper.md
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......@@ -13,12 +13,11 @@ taosKeeper 是 TDengine 3.0 版本监控指标的导出工具，通过简单的
## 安装
<!-- taosKeeper 有两种安装方式: -->
taosKeeper 有两种安装方式：
taosKeeper 安装方式：
<!-- - 安装 TDengine 官方安装包的同时会自动安装 taosKeeper, 详情请参考[ TDengine 安装](/operation/pkg-install)。-->
- 安装 TDengine 官方安装包的同时会自动安装 taosKeeper, 详情请参考[ TDengine 安装](/operation/pkg-install)。
<!-- - 单独编译 taosKeeper 并安装，详情请参考 [taosKeeper](https://github.com/taosdata/taoskeeper) 仓库。-->
- 单独编译 taosKeeper 并安装，详情请参考 [taosKeeper](https://github.com/taosdata/taoskeeper) 仓库。
## 配置和运行方式
......@@ -112,7 +111,7 @@ Active: inactive (dead)
#### 配置文件启动
执行以下命令即可快速体验 taosKeeper。当不指定 taosKeeper 配置文件时，优先使用 `/etc/taos/keeper.toml` 配置，否则将使用默认配置。
执行以下命令即可快速体验 taosKeeper。当不指定 taosKeeper 配置文件时，优先使用 `/etc/taos/keeper.toml` 配置，否则将使用默认配置。
```shell
$ taoskeeper -c <keeper config file>
......@@ -190,19 +189,19 @@ $ curl http://127.0.0.1:6043/metrics
部分结果集：
```shell
# HELP taos_cluster_info_connections_total
# HELP taos_cluster_info_connections_total
# TYPE taos_cluster_info_connections_total counter
taos_cluster_info_connections_total{cluster_id="5981392874047724755"} 16
# HELP taos_cluster_info_dbs_total
# HELP taos_cluster_info_dbs_total
# TYPE taos_cluster_info_dbs_total counter
taos_cluster_info_dbs_total{cluster_id="5981392874047724755"} 2
# HELP taos_cluster_info_dnodes_alive
# HELP taos_cluster_info_dnodes_alive
# TYPE taos_cluster_info_dnodes_alive counter
taos_cluster_info_dnodes_alive{cluster_id="5981392874047724755"} 1
# HELP taos_cluster_info_dnodes_total
# HELP taos_cluster_info_dnodes_total
# TYPE taos_cluster_info_dnodes_total counter
taos_cluster_info_dnodes_total{cluster_id="5981392874047724755"} 1
# HELP taos_cluster_info_first_ep
# HELP taos_cluster_info_first_ep
# TYPE taos_cluster_info_first_ep gauge
taos_cluster_info_first_ep{cluster_id="5981392874047724755",value="hlb:6030"} 1
```
docs/zh/17-operation/03-tolerance.md
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......@@ -19,12 +19,8 @@ TDengine 接收到应用的请求数据包时，先将请求的原始数据包
## 灾备
TDengine 的集群通过多个副本的机制，来提供系统的高可用性，同时具备一定的灾备能力。
TDengine 灾备是通过在异地的两个数据中心中设置两个 TDengine 集群并利用 taosX 的数据复制能力来实现的。假定两个集群为集群 A 和集群 B，其中集群 A 为源集群，承担写入请求并提供查询服务。则在集群 A 所在数据中心中可以配置 taosX 利用 TDengine 提供的数据订阅能力，实时消费集群 A 中新写入的数据，并同步到集群 B。如果发生了灾难导致集群 A 所在数据中心不可用，则可以启用集群 B 作为数据写入和查询的主节点，并在集群 B 所处数据中心中配置 taosX 将数据复制到已经恢复的集群 A 或者新建的集群 C。
TDengine 集群是由 mnode 负责管理的，为保证 mnode 的高可靠，可以配置 三个 mnode 副本。为保证元数据的强一致性，mnode 副本之间通过同步方式进行数据复制，保证了元数据的强一致性。
利用 taosX 的数据复制能力也可以构造出更复杂的灾备方案。
TDengine 集群中的时序数据的副本数是与数据库关联的，一个集群里可以有多个数据库，每个数据库可以配置不同的副本数。创建数据库时，通过参数 replica 指定副本数。为了支持高可靠，需要设置副本数为 3。
TDengine 集群的节点数必须大于等于副本数，否则创建表时将报错。
当 TDengine 集群中的节点部署在不同的物理机上，并设置多个副本数时，就实现了系统的高可靠性，无需再使用其他软件或工具。TDengine 企业版还可以将副本部署在不同机房，从而实现异地容灾。
taosX 只在 TDengine 企业版中提供，关于其具体细节，请联系 business@taosdata.com
tests/pytest/util/sql.py
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......@@ -251,7 +251,7 @@ class TDSql:
if self.queryResult[row][col] != data:
if self.cursor.istype(col, "TIMESTAMP"):
# suppose user want to check nanosecond timestamp if a longer data passed``
# suppose user want to check nanosecond timestamp if a longer data passed``
if isinstance(data,str) :
if (len(data) >= 28):
if self.queryResult[row][col] == _parse_ns_timestamp(data):
......@@ -260,7 +260,7 @@ class TDSql:
else:
caller = inspect.getframeinfo(inspect.stack()[1][0])
args = (caller.filename, caller.lineno, self.sql, row, col, self.queryResult[row][col], data)
tdLog.exit("%s(%d) failed: sql:%s row:%d col:%d data:%s != expect:%s" % args)
tdLog.exit("%s(%d) failed: sql:%s row:%d col:%d data:%s != expect:%s" % args)
else:
if self.queryResult[row][col].astimezone(datetime.timezone.utc) == _parse_datetime(data).astimezone(datetime.timezone.utc):
# tdLog.info(f"sql:{self.sql}, row:{row} col:{col} data:{self.queryResult[row][col]} == expect:{data}")
......@@ -270,12 +270,12 @@ class TDSql:
args = (caller.filename, caller.lineno, self.sql, row, col, self.queryResult[row][col], data)
tdLog.exit("%s(%d) failed: sql:%s row:%d col:%d data:%s != expect:%s" % args)
return
elif isinstance(data,int) :
if len(str(data)) == 16 :
elif isinstance(data,int):
if len(str(data)) == 16:
precision = 'us'
elif len(str(data)) == 13 :
elif len(str(data)) == 13:
precision = 'ms'
elif len(str(data)) == 19 :
elif len(str(data)) == 19:
precision = 'ns'
else:
caller = inspect.getframeinfo(inspect.stack()[1][0])
......@@ -303,11 +303,21 @@ class TDSql:
args = (caller.filename, caller.lineno, self.sql, row, col, self.queryResult[row][col], data)
tdLog.exit("%s(%d) failed: sql:%s row:%d col:%d data:%s != expect:%s" % args)
return
elif isinstance(data,datetime.datetime):
dt_obj = self.queryResult[row][col]
delt_data = data-datetime.datetime.fromtimestamp(0,data.tzinfo)
delt_result = self.queryResult[row][col] - datetime.datetime.fromtimestamp(0,self.queryResult[row][col].tzinfo)
if delt_data == delt_result:
tdLog.info("check successfully")
else:
caller = inspect.getframeinfo(inspect.stack()[1][0])
args = (caller.filename, caller.lineno, self.sql, row, col, self.queryResult[row][col], data)
tdLog.exit("%s(%d) failed: sql:%s row:%d col:%d data:%s != expect:%s" % args)
return
else:
caller = inspect.getframeinfo(inspect.stack()[1][0])
args = (caller.filename, caller.lineno, self.sql, row, col, self.queryResult[row][col], data)
tdLog.exit("%s(%d) failed: sql:%s row:%d col:%d data:%s != expect:%s" % args)
if str(self.queryResult[row][col]) == str(data):
# tdLog.info(f"sql:{self.sql}, row:{row} col:{col} data:{self.queryResult[row][col]} == expect:{data}")
......
tests/system-test/2-query/cast.py
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......@@ -38,11 +38,8 @@ class TDTestCase:
if data_tb_col[i] is None:
tdSql.checkData( i, 0 , None )
if col_name not in ["c2", "double"] or tbname != f"{self.dbname}.t1" or i != 10:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(data_tb_col[i]/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = datetime.datetime.fromtimestamp(data_tb_col[i]/1000)
tdSql.checkData( i, 0, date_init_stamp)
def __range_to_timestamp(self, cols, tables):
for col in cols:
......@@ -60,7 +57,7 @@ class TDTestCase:
self.__range_to_timestamp(cols=__col_list, tables=__table_list)
def all_test(self):
_datetime_epoch = datetime.datetime.fromtimestamp(0)
tdSql.query(f"select c1 from {self.dbname}.ct4")
data_ct4_c1 = [tdSql.getData(i,0) for i in range(tdSql.queryRows)]
tdSql.query(f"select c1 from {self.dbname}.t1")
......@@ -99,22 +96,16 @@ class TDTestCase:
if data_ct4_c1[i] is None:
tdSql.checkData( i, 0 , None )
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(data_ct4_c1[i]/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_ct4_c1[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdSql.query(f"select cast(c1 as timestamp) as b from {self.dbname}.t1")
for i in range(len(data_t1_c1)):
if data_t1_c1[i] is None:
tdSql.checkData( i, 0 , None )
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(data_t1_c1[i]/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_t1_c1[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdLog.printNoPrefix("==========step8: cast bigint to bigint, expect no changes")
......@@ -156,11 +147,8 @@ class TDTestCase:
if data_ct4_c2[i] is None:
tdSql.checkData( i, 0 , None )
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(data_ct4_c2[i]/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_ct4_c2[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdSql.query(f"select cast(c2 as timestamp) as b from {self.dbname}.t1")
......@@ -170,11 +158,8 @@ class TDTestCase:
elif i == 10:
continue
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(data_t1_c2[i]/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_t1_c2[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdLog.printNoPrefix("==========step12: cast smallint to bigint, expect no changes")
......@@ -216,22 +201,16 @@ class TDTestCase:
if data_ct4_c3[i] is None:
tdSql.checkData( i, 0 , None )
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(data_ct4_c3[i]/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_ct4_c3[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdSql.query(f"select cast(c3 as timestamp) as b from {self.dbname}.t1")
for i in range(len(data_t1_c3)):
if data_t1_c3[i] is None:
tdSql.checkData( i, 0 , None )
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(data_t1_c3[i]/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_t1_c3[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdLog.printNoPrefix("==========step16: cast tinyint to bigint, expect no changes")
......@@ -273,22 +252,16 @@ class TDTestCase:
if data_ct4_c4[i] is None:
tdSql.checkData( i, 0 , None )
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(data_ct4_c4[i]/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_ct4_c4[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdSql.query(f"select cast(c4 as timestamp) as b from {self.dbname}.t1")
for i in range(len(data_t1_c4)):
if data_t1_c4[i] is None:
tdSql.checkData( i, 0 , None )
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(data_t1_c4[i]/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_t1_c4[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdLog.printNoPrefix("==========step20: cast float to bigint, expect no changes")
......@@ -326,21 +299,15 @@ class TDTestCase:
if data_ct4_c5[i] is None:
tdSql.checkData( i, 0 , None )
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(int(data_ct4_c5[i])/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_ct4_c5[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdSql.query(f"select cast(c5 as timestamp) as b from {self.dbname}.t1")
for i in range(len(data_t1_c5)):
if data_t1_c5[i] is None:
tdSql.checkData( i, 0 , None )
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(int(data_t1_c5[i])/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_t1_c5[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdLog.printNoPrefix("==========step24: cast double to bigint, expect no changes")
tdSql.query(f"select c6 from {self.dbname}.ct4")
......@@ -382,11 +349,8 @@ class TDTestCase:
if data_ct4_c6[i] is None:
tdSql.checkData( i, 0 , None )
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(int(data_ct4_c6[i])/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_ct4_c6[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdSql.query(f"select cast(c6 as timestamp) as b from {self.dbname}.t1")
for i in range(len(data_t1_c6)):
......@@ -395,11 +359,8 @@ class TDTestCase:
elif i == 10:
continue
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(int(data_t1_c6[i])/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_t1_c6[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdLog.printNoPrefix("==========step28: cast bool to bigint, expect no changes")
tdSql.query(f"select c7 from {self.dbname}.ct4")
......@@ -436,21 +397,15 @@ class TDTestCase:
if data_ct4_c7[i] is None:
tdSql.checkData( i, 0 , None )
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(int(data_ct4_c7[i])/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_ct4_c7[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdSql.query(f"select cast(c7 as timestamp) as b from {self.dbname}.t1")
for i in range(len(data_t1_c7)):
if data_t1_c7[i] is None:
tdSql.checkData( i, 0 , None )
else:
utc_zone = datetime.timezone.utc
utc_8 = datetime.timezone(datetime.timedelta(hours=8))
date_init_stamp = datetime.datetime.utcfromtimestamp(int(data_t1_c7[i])/1000)
date_data = date_init_stamp.replace(tzinfo=utc_zone).astimezone(utc_8).strftime("%Y-%m-%d %H:%M:%S.%f")
tdSql.checkData( i, 0, date_data)
date_init_stamp = _datetime_epoch+datetime.timedelta(seconds=int(data_t1_c7[i]) / 1000.0)
tdSql.checkData( i, 0, date_init_stamp)
tdSql.query(f"select c8 from {self.dbname}.ct4")
......@@ -694,7 +649,7 @@ class TDTestCase:
tdSql.query(f"select cast('123' as tinyint unsigned) as b from {self.dbname}.stb1 partition by tbname")
# uion with cast and common cols
tdSql.query(f"select cast(c2 as int) as b from {self.dbname}.stb1 union all select c1 from {self.dbname}.stb1 ")
tdSql.query(f"select cast(c3 as bool) as b from {self.dbname}.stb1 union all select c7 from {self.dbname}.ct1 ")
tdSql.query(f"select cast(c4 as tinyint) as b from {self.dbname}.stb1 union all select c4 from {self.dbname}.stb1")
......
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