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The following commit(s) were added to refs/heads/main by this push:
new fcf64df fix the rest bad urls (#210)
fcf64df is described below
commit fcf64df90df63b98b61d3da1d6c2f8f8d8ef86c7
Author: wanghui42 <[email protected]>
AuthorDate: Fri Mar 29 18:50:02 2024 +0800
fix the rest bad urls (#210)
---
.../Security-Management.md | 4 +-
.../Security-Management_timecho.md | 4 +-
src/UserGuide/Master/Reference/UDF-Libraries.md | 4 +-
src/UserGuide/Master/SQL-Manual/SQL-Manual.md | 54 +++---
.../Master/User-Manual/Database-Programming.md | 38 ++---
src/UserGuide/Master/User-Manual/Delete-Data.md | 181 ---------------------
.../Master/User-Manual/Write-Delete-Data.md | 8 +-
.../Security-Management.md | 4 +-
.../Security-Management_timecho.md | 4 +-
src/UserGuide/latest/Reference/UDF-Libraries.md | 4 +-
src/UserGuide/latest/SQL-Manual/SQL-Manual.md | 24 +--
.../latest/User-Manual/Database-Programming.md | 38 ++---
src/UserGuide/latest/User-Manual/Delete-Data.md | 181 ---------------------
.../latest/User-Manual/Write-Delete-Data.md | 8 +-
src/zh/Download/README.md | 2 +-
15 files changed, 98 insertions(+), 460 deletions(-)
diff --git
a/src/UserGuide/Master/Deployment-and-Maintenance/Security-Management.md
b/src/UserGuide/Master/Deployment-and-Maintenance/Security-Management.md
index bdb3d4b..7c873b6 100644
--- a/src/UserGuide/Master/Deployment-and-Maintenance/Security-Management.md
+++ b/src/UserGuide/Master/Deployment-and-Maintenance/Security-Management.md
@@ -25,7 +25,7 @@
IoTDB provides users with account privilege management operations, so as to
ensure data security.
-We will show you basic user privilege management operations through the
following specific examples. Detailed SQL syntax and usage details can be found
in [SQL Documentation](../Reference/SQL-Reference.md).
+We will show you basic user privilege management operations through the
following specific examples. Detailed SQL syntax and usage details can be found
in [SQL Documentation](../SQL-Manual/SQL-Manual.md).
At the same time, in the JAVA programming environment, you can use the [Java
JDBC](../API/Programming-JDBC.md) to execute privilege management statements in
a single or batch mode.
### Basic Concepts
@@ -372,7 +372,7 @@ At the same time, changes to roles are immediately
reflected on all users who ow
| CREATE\_TIMESERIES | create timeseries; path dependent
|
Eg1: create timeseries<br />`create timeseries root.ln.wf02.status with
datatype=BOOLEAN,encoding=PLAIN;`<br />Eg2: create aligned timeseries<br
/>`create aligned timeseries root.ln.device1(latitude FLOAT encoding=PLAIN
compressor=SNAPPY, longitude FLOAT encoding=PLAIN compressor=SNAPPY);`
[...]
| INSERT\_TIMESERIES | insert data; path dependent
|
Eg1: `insert into root.ln.wf02(timestamp,status) values(1,true);`<br />Eg2:
`insert into root.sg1.d1(time, s1, s2) aligned values(1, 1, 1)`
[...]
| ALTER\_TIMESERIES | alter timeseries; path dependent
|
Eg1: `alter timeseries root.turbine.d1.s1 ADD TAGS tag3=v3, tag4=v4;`<br />Eg2:
`ALTER timeseries root.turbine.d1.s1 UPSERT ALIAS=newAlias TAGS(tag2=newV2,
tag3=v3) ATTRIBUTES(attr3=v3, attr4=v4);`
[...]
-| READ\_TIMESERIES | query data; path dependent
|
Eg1: `SHOW DATABASES;` <br />Eg2: `show child paths root.ln, show child nodes
root.ln;`<br />Eg3: `show devices;`<br />Eg4: `show timeseries root.**;`<br
/>Eg5: `show schema templates;`<br />Eg6: `show all ttl`<br />Eg7:
[Query-Data](../Query-Data/Overview.md)（The query statements under this section
all use this permission）<br />Eg [...]
+| READ\_TIMESERIES | query data; path dependent
|
Eg1: `SHOW DATABASES;` <br />Eg2: `show child paths root.ln, show child nodes
root.ln;`<br />Eg3: `show devices;`<br />Eg4: `show timeseries root.**;`<br
/>Eg5: `show schema templates;`<br />Eg6: `show all ttl`<br />Eg7:
[Query-Data](../User-Manual/Query-Data.md)（The query statements under this
section all use this permission）<br / [...]
| DELETE\_TIMESERIES | delete data or timeseries; path dependent
|
Eg1: delete timeseries<br />`delete timeseries root.ln.wf01.wt01.status`<br
/>Eg2: delete data<br />`delete from root.ln.wf02.wt02.status where time <
10`<br />Eg3: use drop semantic<br />`drop timeseries root.ln.wf01.wt01.status
[...]
| CREATE\_USER | create users; path independent
|
Eg: `create user thulab 'passwd';`
[...]
| DELETE\_USER | delete users; path independent
|
Eg: `drop user xiaoming;`
[...]
diff --git
a/src/UserGuide/Master/Deployment-and-Maintenance/Security-Management_timecho.md
b/src/UserGuide/Master/Deployment-and-Maintenance/Security-Management_timecho.md
index 9bb3593..13e25b0 100644
---
a/src/UserGuide/Master/Deployment-and-Maintenance/Security-Management_timecho.md
+++
b/src/UserGuide/Master/Deployment-and-Maintenance/Security-Management_timecho.md
@@ -33,7 +33,7 @@ TODO
IoTDB provides users with account privilege management operations, so as to
ensure data security.
-We will show you basic user privilege management operations through the
following specific examples. Detailed SQL syntax and usage details can be found
in [SQL Documentation](../Reference/SQL-Reference.md).
+We will show you basic user privilege management operations through the
following specific examples. Detailed SQL syntax and usage details can be found
in [SQL Documentation](../SQL-Manual/SQL-Manual.md).
At the same time, in the JAVA programming environment, you can use the [Java
JDBC](../API/Programming-JDBC.md) to execute privilege management statements in
a single or batch mode.
### Basic Concepts
@@ -380,7 +380,7 @@ At the same time, changes to roles are immediately
reflected on all users who ow
| CREATE\_TIMESERIES | create timeseries; path dependent
|
Eg1: create timeseries<br />`create timeseries root.ln.wf02.status with
datatype=BOOLEAN,encoding=PLAIN;`<br />Eg2: create aligned timeseries<br
/>`create aligned timeseries root.ln.device1(latitude FLOAT encoding=PLAIN
compressor=SNAPPY, longitude FLOAT encoding=PLAIN compressor=SNAPPY);`
[...]
| INSERT\_TIMESERIES | insert data; path dependent
|
Eg1: `insert into root.ln.wf02(timestamp,status) values(1,true);`<br />Eg2:
`insert into root.sg1.d1(time, s1, s2) aligned values(1, 1, 1)`
[...]
| ALTER\_TIMESERIES | alter timeseries; path dependent
|
Eg1: `alter timeseries root.turbine.d1.s1 ADD TAGS tag3=v3, tag4=v4;`<br />Eg2:
`ALTER timeseries root.turbine.d1.s1 UPSERT ALIAS=newAlias TAGS(tag2=newV2,
tag3=v3) ATTRIBUTES(attr3=v3, attr4=v4);`
[...]
-| READ\_TIMESERIES | query data; path dependent
|
Eg1: `SHOW DATABASES;` <br />Eg2: `show child paths root.ln, show child nodes
root.ln;`<br />Eg3: `show devices;`<br />Eg4: `show timeseries root.**;`<br
/>Eg5: `show schema templates;`<br />Eg6: `show all ttl`<br />Eg7:
[Query-Data](../Query-Data/Overview.md)（The query statements under this section
all use this permission）<br />Eg [...]
+| READ\_TIMESERIES | query data; path dependent
|
Eg1: `SHOW DATABASES;` <br />Eg2: `show child paths root.ln, show child nodes
root.ln;`<br />Eg3: `show devices;`<br />Eg4: `show timeseries root.**;`<br
/>Eg5: `show schema templates;`<br />Eg6: `show all ttl`<br />Eg7:
[Query-Data](../User-Manual/Query-Data.md)（The query statements under this
section all use this permission）<br / [...]
| DELETE\_TIMESERIES | delete data or timeseries; path dependent
|
Eg1: delete timeseries<br />`delete timeseries root.ln.wf01.wt01.status`<br
/>Eg2: delete data<br />`delete from root.ln.wf02.wt02.status where time <
10`<br />Eg3: use drop semantic<br />`drop timeseries root.ln.wf01.wt01.status
[...]
| CREATE\_USER | create users; path independent
|
Eg: `create user thulab 'passwd';`
[...]
| DELETE\_USER | delete users; path independent
|
Eg: `drop user xiaoming;`
[...]
diff --git a/src/UserGuide/Master/Reference/UDF-Libraries.md
b/src/UserGuide/Master/Reference/UDF-Libraries.md
index 9eadaba..79599e2 100644
--- a/src/UserGuide/Master/Reference/UDF-Libraries.md
+++ b/src/UserGuide/Master/Reference/UDF-Libraries.md
@@ -604,14 +604,14 @@ Output series:
This function is used to calculate the auto-correlation factor of the input
time series,
which equals to cross correlation between the same series.
-For more information, please refer to [XCorr](./Data-Matching.md#XCorr)
function.
+For more information, please refer to [XCorr](./UDF-Libraries.md#XCorr)
function.
**Name:** ACF
**Input Series:** Only support a single input numeric series. The type is
INT32 / INT64 / FLOAT / DOUBLE.
**Output Series:** Output a single series. The type is DOUBLE.
-There are $2N-1$ data points in the series, and the values are interpreted in
details in [XCorr](./Data-Matching.md#XCorr) function.
+There are $2N-1$ data points in the series, and the values are interpreted in
details in [XCorr](./UDF-Libraries.md#XCorr) function.
**Note:**
diff --git a/src/UserGuide/Master/SQL-Manual/SQL-Manual.md
b/src/UserGuide/Master/SQL-Manual/SQL-Manual.md
index deb1170..8d3f4d0 100644
--- a/src/UserGuide/Master/SQL-Manual/SQL-Manual.md
+++ b/src/UserGuide/Master/SQL-Manual/SQL-Manual.md
@@ -913,7 +913,7 @@ For more details, see document
[Operator-and-Expression](../User-Manual/Operator
### Arithmetic Operators
-For details and examples, see the document [Arithmetic Operators and
Functions](../Operators-Functions/Mathematical.md).
+For details and examples, see the document [Arithmetic Operators and
Functions](../Reference/Function-and-Expression.md#arithmetic-operators-and-functions).
```sql
select s1, - s1, s2, + s2, s1 + s2, s1 - s2, s1 * s2, s1 / s2, s1 % s2 from
root.sg.d1
@@ -921,7 +921,7 @@ select s1, - s1, s2, + s2, s1 + s2, s1 - s2, s1 * s2, s1 /
s2, s1 % s2 from root
### Comparison Operators
-For details and examples, see the document [Comparison Operators and
Functions](../Operators-Functions/Comparison.md).
+For details and examples, see the document [Comparison Operators and
Functions](../Reference/Function-and-Expression.md#comparison-operators-and-functions).
```sql
# Basic comparison operators
@@ -952,7 +952,7 @@ select a, a in (1, 2) from root.test;
### Logical Operators
-For details and examples, see the document [Logical
Operators](../Operators-Functions/Logical.md).
+For details and examples, see the document [Logical
Operators](../Reference/Function-and-Expression.md#logical-operators).
```sql
select a, b, a > 10, a <= b, !(a <= b), a > 10 && a > b from root.test;
@@ -960,11 +960,11 @@ select a, b, a > 10, a <= b, !(a <= b), a > 10 && a > b
from root.test;
## BUILT-IN FUNCTIONS
-For more details, see document
[Operator-and-Expression](../User-Manual/Operator-and-Expression.md).
+For more details, see document
[Operator-and-Expression](../Reference/Function-and-Expression.md).
### Aggregate Functions
-For details and examples, see the document [Aggregate
Functions](../Operators-Functions/Aggregation.md).
+For details and examples, see the document [Aggregate
Functions](../Reference/Function-and-Expression.md#aggregate-functions).
```sql
select count(status) from root.ln.wf01.wt01;
@@ -977,7 +977,7 @@ select time_duration(s1) from root.db.d1;
### Arithmetic Functions
-For details and examples, see the document [Arithmetic Operators and
Functions](../Operators-Functions/Mathematical.md).
+For details and examples, see the document [Arithmetic Operators and
Functions](../Reference/Function-and-Expression.md#arithmetic-operators-and-functions).
```sql
select s1, sin(s1), cos(s1), tan(s1) from root.sg1.d1 limit 5 offset 1000;
@@ -986,7 +986,7 @@ select s4,round(s4),round(s4,2),round(s4,-1) from
root.sg1.d1;
### Comparison Functions
-For details and examples, see the document [Comparison Operators and
Functions](../Operators-Functions/Comparison.md).
+For details and examples, see the document [Comparison Operators and
Functions](../Reference/Function-and-Expression.md#comparison-operators-and-functions).
```sql
select ts, on_off(ts, 'threshold'='2') from root.test;
@@ -995,7 +995,7 @@ select ts, in_range(ts, 'lower'='2', 'upper'='3.1') from
root.test;
### String Processing Functions
-For details and examples, see the document [String
Processing](../Operators-Functions/String.md).
+For details and examples, see the document [String
Processing](../Reference/Function-and-Expression.md#string-processing).
```sql
select s1, string_contains(s1, 's'='warn') from root.sg1.d4;
@@ -1023,7 +1023,7 @@ select regexsplit(s1, "regex"=",", "index"="3") from
root.test.d1
### Data Type Conversion Function
-For details and examples, see the document [Data Type Conversion
Function](../Operators-Functions/Conversion.md).
+For details and examples, see the document [Data Type Conversion
Function](../Reference/Function-and-Expression.md#data-type-conversion-function).
```sql
SELECT cast(s1 as INT32) from root.sg
@@ -1031,7 +1031,7 @@ SELECT cast(s1 as INT32) from root.sg
### Constant Timeseries Generating Functions
-For details and examples, see the document [Constant Timeseries Generating
Functions](../Operators-Functions/Constant.md).
+For details and examples, see the document [Constant Timeseries Generating
Functions](../Reference/Function-and-Expression.md#constant-timeseries-generating-functions).
```sql
select s1, s2, const(s1, 'value'='1024', 'type'='INT64'), pi(s2), e(s1, s2)
from root.sg1.d1;
@@ -1039,7 +1039,7 @@ select s1, s2, const(s1, 'value'='1024', 'type'='INT64'),
pi(s2), e(s1, s2) from
### Selector Functions
-For details and examples, see the document [Selector
Functions](../Operators-Functions/Selection.md).
+For details and examples, see the document [Selector
Functions](../Reference/Function-and-Expression.md#selector-functions).
```sql
select s1, top_k(s1, 'k'='2'), bottom_k(s1, 'k'='2') from root.sg1.d2 where
time > 2020-12-10T20:36:15.530+08:00;
@@ -1047,7 +1047,7 @@ select s1, top_k(s1, 'k'='2'), bottom_k(s1, 'k'='2') from
root.sg1.d2 where time
### Continuous Interval Functions
-For details and examples, see the document [Continuous Interval
Functions](../Operators-Functions/Continuous-Interval.md).
+For details and examples, see the document [Continuous Interval
Functions](../Reference/Function-and-Expression.md#continuous-interval-functions).
```sql
select s1, zero_count(s1), non_zero_count(s2), zero_duration(s3),
non_zero_duration(s4) from root.sg.d2;
@@ -1055,7 +1055,7 @@ select s1, zero_count(s1), non_zero_count(s2),
zero_duration(s3), non_zero_durat
### Variation Trend Calculation Functions
-For details and examples, see the document [Variation Trend Calculation
Functions](../Operators-Functions/Variation-Trend.md).
+For details and examples, see the document [Variation Trend Calculation
Functions](../Reference/Function-and-Expression.md#variation-trend-calculation-functions).
```sql
select s1, time_difference(s1), difference(s1), non_negative_difference(s1),
derivative(s1), non_negative_derivative(s1) from root.sg1.d1 limit 5 offset
1000;
@@ -1066,7 +1066,7 @@ SELECT DIFF(s1, 'ignoreNull'='false'), DIFF(s2,
'ignoreNull'='false') from root.
### Sample Functions
-For details and examples, see the document [Sample
Functions](../Operators-Functions/Sample.md).
+For details and examples, see the document [Sample
Functions](../Reference/Function-and-Expression.md#sample-functions).
```sql
select equal_size_bucket_random_sample(temperature,'proportion'='0.1') as
random_sample from root.ln.wf01.wt01;
@@ -1080,7 +1080,7 @@ select M4(s1,'windowSize'='10') from root.vehicle.d1
### Change Points Function
-For details and examples, see the document
[Time-Series](../Operators-Functions/Time-Series.md).
+For details and examples, see the document
[Time-Series](../Reference/Function-and-Expression.md#time-series-processing).
```sql
select change_points(s1), change_points(s2), change_points(s3),
change_points(s4), change_points(s5), change_points(s6) from
root.testChangePoints.d1
@@ -1088,11 +1088,11 @@ select change_points(s1), change_points(s2),
change_points(s3), change_points(s4
## DATA QUALITY FUNCTION LIBRARY
-For more details, see document
[Operator-and-Expression](../User-Manual/Operator-and-Expression.md).
+For more details, see document
[Operator-and-Expression](../Reference/UDF-Libraries.md#).
### Data Quality
-For details and examples, see the document
[Data-Quality](../Operators-Functions/Data-Quality.md).
+For details and examples, see the document
[Data-Quality](../Reference/UDF-Libraries.md#data-quality).
```sql
# Completeness
@@ -1117,7 +1117,7 @@ select Accuracy(t1,t2,t3,m1,m2,m3) from root.test
### Data Profiling
-For details and examples, see the document
[Data-Profiling](../Operators-Functions/Data-Profiling.md).
+For details and examples, see the document
[Data-Profiling](../Reference/UDF-Libraries.md#data-profiling).
```sql
# ACF
@@ -1197,7 +1197,7 @@ select zscore(s1) from root.test
### Anomaly Detection
-For details and examples, see the document
[Anomaly-Detection](../Operators-Functions/Anomaly-Detection.md).
+For details and examples, see the document
[Anomaly-Detection](../Reference/UDF-Libraries.md#anomaly-detection).
```sql
# IQR
@@ -1232,7 +1232,7 @@ select
MasterDetect(lo,la,m_lo,m_la,model,'output_type'='anomaly','p'='3','k'='3
### Frequency Domain
-For details and examples, see the document
[Frequency-Domain](../Operators-Functions/Frequency-Domain.md).
+For details and examples, see the document
[Frequency-Domain](../Reference/UDF-Libraries.md#frequency-domain-analysis).
```sql
# Conv
@@ -1261,7 +1261,7 @@ select lowpass(s1,'wpass'='0.45') from root.test.d1
### Data Matching
-For details and examples, see the document
[Data-Matching](../Operators-Functions/Data-Matching.md).
+For details and examples, see the document
[Data-Matching](../Reference/UDF-Libraries.md#data-matching).
```sql
# Cov
@@ -1282,7 +1282,7 @@ select xcorr(s1, s2) from root.test.d1 where time <=
2020-01-01 00:00:05
### Data Repairing
-For details and examples, see the document
[Data-Repairing](../Operators-Functions/Data-Repairing.md).
+For details and examples, see the document
[Data-Repairing](../Reference/UDF-Libraries.md#data-repairing).
```sql
# TimestampRepair
@@ -1307,7 +1307,7 @@ select seasonalrepair(s1,'method'='improved','period'=3)
from root.test.d2
### Series Discovery
-For details and examples, see the document
[Series-Discovery](../Operators-Functions/Series-Discovery.md).
+For details and examples, see the document
[Series-Discovery](../Reference/UDF-Libraries.md#series-discovery).
```sql
# ConsecutiveSequences
@@ -1320,7 +1320,7 @@ select consecutivewindows(s1,s2,'length'='10m') from
root.test.d1
### Machine Learning
-For details and examples, see the document
[Machine-Learning](../Operators-Functions/Machine-Learning.md).
+For details and examples, see the document
[Machine-Learning](../Reference/UDF-Libraries.md#machine-learning).
```sql
# AR
@@ -1335,7 +1335,7 @@ select rm(s0, s1,"tb"="3","vb"="2") from root.test.d0
## LAMBDA EXPRESSION
-For details and examples, see the document
[Lambda](../Operators-Functions/Lambda.md).
+For details and examples, see the document
[Lambda](../Reference/Function-and-Expression#lambda-expression).
```sql
select jexl(temperature, 'expr'='x -> {x + x}') as jexl1, jexl(temperature,
'expr'='x -> {x * 3}') as jexl2, jexl(temperature, 'expr'='x -> {x * x}') as
jexl3, jexl(temperature, 'expr'='x -> {multiply(x, 100)}') as jexl4,
jexl(temperature, st, 'expr'='(x, y) -> {x + y}') as jexl5, jexl(temperature,
st, str, 'expr'='(x, y, z) -> {x + y + z}') as jexl6 from root.ln.wf01.wt01;```
@@ -1343,7 +1343,7 @@ select jexl(temperature, 'expr'='x -> {x + x}') as jexl1,
jexl(temperature, 'exp
## CONDITIONAL EXPRESSION
-For details and examples, see the document [Conditional
Expressions](../Operators-Functions/Conditional.md).
+For details and examples, see the document [Conditional
Expressions](../Reference/Function-and-Expression#conditional-expressions).
```sql
select T, P, case
@@ -1543,7 +1543,7 @@ CQs can't be altered once they're created. To change a
CQ, you must `DROP` and r
## USER-DEFINED FUNCTION (UDF)
-For more details, see document
[Operator-and-Expression](../User-Manual/Operator-and-Expression.md).
+For more details, see document
[Operator-and-Expression](../Reference/UDF-Libraries.md).
### UDF Registration
diff --git a/src/UserGuide/Master/User-Manual/Database-Programming.md
b/src/UserGuide/Master/User-Manual/Database-Programming.md
index 121ef4a..dc21d4d 100644
--- a/src/UserGuide/Master/User-Manual/Database-Programming.md
+++ b/src/UserGuide/Master/User-Manual/Database-Programming.md
@@ -1875,17 +1875,17 @@ When you have prepared the UDF source code, test cases,
and instructions, you ar
#### Built-in UDF
-1. Aggregate Functions, such as `SUM`. For details and examples, see the
document [Aggregate Functions](../Operators-Functions/Aggregation.md).
-2. Arithmetic Functions, such as `SIN`. For details and examples, see the
document [Arithmetic Operators and
Functions](../Operators-Functions/Mathematical.md).
-3. Comparison Functions, such as `ON_OFF`. For details and examples, see the
document [Comparison Operators and
Functions](../Operators-Functions/Comparison.md).
-4. String Processing Functions, such as `STRING_CONTAINS`. For details and
examples, see the document [String
Processing](../Operators-Functions/String.md).
-5. Data Type Conversion Function, such as `CAST`. For details and examples,
see the document [Data Type Conversion
Function](../Operators-Functions/Conversion.md).
-6. Constant Timeseries Generating Functions, such as `CONST`. For details
and examples, see the document [Constant Timeseries Generating
Functions](../Operators-Functions/Constant.md).
-7. Selector Functions, such as `TOP_K`. For details and examples, see the
document [Selector Functions](../Operators-Functions/Selection.md).
-8. Continuous Interval Functions, such as `ZERO_DURATION`. For details and
examples, see the document [Continuous Interval
Functions](../Operators-Functions/Continuous-Interval.md).
-9. Variation Trend Calculation Functions, such as `TIME_DIFFERENCE`. For
details and examples, see the document [Variation Trend Calculation
Functions](../Operators-Functions/Variation-Trend.md).
-10. Sample Functions, such as `M4`. For details and examples, see the
document [Sample Functions](../Operators-Functions/Sample.md).
-11. Change Points Function, such as `CHANGE_POINTS`. For details and
examples, see the document [Time-Series](../Operators-Functions/Time-Series.md).
+1. Aggregate Functions, such as `SUM`. For details and examples, see the
document [Aggregate
Functions](../Reference/Function-and-Expression.md#aggregate-functions).
+2. Arithmetic Functions, such as `SIN`. For details and examples, see the
document [Arithmetic Operators and
Functions](../Reference/Function-and-Expression.md#arithmetic-operators-and-functions).
+3. Comparison Functions, such as `ON_OFF`. For details and examples, see the
document [Comparison Operators and
Functions](../Reference/Function-and-Expression.md#comparison-operators-and-functions).
+4. String Processing Functions, such as `STRING_CONTAINS`. For details and
examples, see the document [String
Processing](../Reference/Function-and-Expression.md#string-processing).
+5. Data Type Conversion Function, such as `CAST`. For details and examples,
see the document [Data Type Conversion
Function](../Reference/Function-and-Expression.md#data-type-conversion-function).
+6. Constant Timeseries Generating Functions, such as `CONST`. For details
and examples, see the document [Constant Timeseries Generating
Functions](../Reference/Function-and-Expression.md#constant-timeseries-generating-functions).
+7. Selector Functions, such as `TOP_K`. For details and examples, see the
document [Selector
Functions](../Reference/Function-and-Expression.md#selector-functions).
+8. Continuous Interval Functions, such as `ZERO_DURATION`. For details and
examples, see the document [Continuous Interval
Functions](../Reference/Function-and-Expression.md#continuous-interval-functions).
+9. Variation Trend Calculation Functions, such as `TIME_DIFFERENCE`. For
details and examples, see the document [Variation Trend Calculation
Functions](../Reference/Function-and-Expression.md#variation-trend-calculation-functions).
+10. Sample Functions, such as `M4`. For details and examples, see the
document [Sample
Functions](../Reference/Function-and-Expression.md#sample-functions).
+11. Change Points Function, such as `CHANGE_POINTS`. For details and
examples, see the document
[Time-Series](../Reference/Function-and-Expression.md#time-series-processing).
#### Data Quality Function Library
@@ -1904,14 +1904,14 @@ The functions in this function library are not built-in
functions, and must be l
##### Implemented Functions
-1. Data Quality related functions, such as `Completeness`. For details and
examples, see the document
[Data-Quality](../Operators-Functions/Data-Quality.md).
-2. Data Profiling related functions, such as `ACF`. For details and
examples, see the document
[Data-Profiling](../Operators-Functions/Data-Profiling.md).
-3. Anomaly Detection related functions, such as `IQR`. For details and
examples, see the document
[Anomaly-Detection](../Operators-Functions/Anomaly-Detection.md).
-4. Frequency Domain Analysis related functions, such as `Conv`. For details
and examples, see the document
[Frequency-Domain](../Operators-Functions/Frequency-Domain.md).
-5. Data Matching related functions, such as `DTW`. For details and examples,
see the document [Data-Matching](../Operators-Functions/Data-Matching.md).
-6. Data Repairing related functions, such as `TimestampRepair`. For details
and examples, see the document
[Data-Repairing](../Operators-Functions/Data-Repairing.md).
-7. Series Discovery related functions, such as `ConsecutiveSequences`. For
details and examples, see the document
[Series-Discovery](../Operators-Functions/Series-Discovery.md).
-8. Machine Learning related functions, such as `AR`. For details and
examples, see the document
[Machine-Learning](../Operators-Functions/Machine-Learning.md).
+1. Data Quality related functions, such as `Completeness`. For details and
examples, see the document
[Data-Quality](../Reference/UDF-Libraries.md#data-quality).
+2. Data Profiling related functions, such as `ACF`. For details and
examples, see the document
[Data-Profiling](../Reference/UDF-Libraries.md#data-profiling).
+3. Anomaly Detection related functions, such as `IQR`. For details and
examples, see the document
[Anomaly-Detection](../Reference/UDF-Libraries.md#anomaly-detection).
+4. Frequency Domain Analysis related functions, such as `Conv`. For details
and examples, see the document
[Frequency-Domain](../Reference/UDF-Libraries.md#frequency-domain-analysis).
+5. Data Matching related functions, such as `DTW`. For details and examples,
see the document [Data-Matching](../Reference/UDF-Libraries.md#data-matching).
+6. Data Repairing related functions, such as `TimestampRepair`. For details
and examples, see the document
[Data-Repairing](../Reference/UDF-Libraries.md#data-repairing).
+7. Series Discovery related functions, such as `ConsecutiveSequences`. For
details and examples, see the document
[Series-Discovery](../Reference/UDF-Libraries.md#series-discovery).
+8. Machine Learning related functions, such as `AR`. For details and
examples, see the document
[Machine-Learning](../Reference/UDF-Libraries.md#machine-learning).
### Q&A
diff --git a/src/UserGuide/Master/User-Manual/Delete-Data.md
b/src/UserGuide/Master/User-Manual/Delete-Data.md
deleted file mode 100644
index 05d3ad1..0000000
--- a/src/UserGuide/Master/User-Manual/Delete-Data.md
+++ /dev/null
@@ -1,181 +0,0 @@
-<!--
-
- Licensed to the Apache Software Foundation (ASF) under one
- or more contributor license agreements. See the NOTICE file
- distributed with this work for additional information
- regarding copyright ownership. The ASF licenses this file
- to you under the Apache License, Version 2.0 (the
- "License"); you may not use this file except in compliance
- with the License. You may obtain a copy of the License at
-
- http://www.apache.org/licenses/LICENSE-2.0
-
- Unless required by applicable law or agreed to in writing,
- software distributed under the License is distributed on an
- "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
- KIND, either express or implied. See the License for the
- specific language governing permissions and limitations
- under the License.
-
--->
-
-# DELETE
-
-Users can delete data that meet the deletion condition in the specified
timeseries by using the [DELETE statement](../Reference/SQL-Reference.md). When
deleting data, users can select one or more timeseries paths, prefix paths, or
paths with star to delete data within a certain time interval.
-
-In a JAVA programming environment, you can use the [Java
JDBC](../API/Programming-JDBC.md) to execute single or batch UPDATE statements.
-
-## Delete Single Timeseries
-
-Taking ln Group as an example, there exists such a usage scenario:
-
-The wf02 plant's wt02 device has many segments of errors in its power supply
status before 2017-11-01 16:26:00, and the data cannot be analyzed correctly.
The erroneous data affected the correlation analysis with other devices. At
this point, the data before this time point needs to be deleted. The SQL
statement for this operation is
-
-```sql
-delete from root.ln.wf02.wt02.status where time<=2017-11-01T16:26:00;
-```
-
-In case we hope to merely delete the data before 2017-11-01 16:26:00 in the
year of 2017, The SQL statement is:
-
-```sql
-delete from root.ln.wf02.wt02.status where time>=2017-01-01T00:00:00 and
time<=2017-11-01T16:26:00;
-```
-
-IoTDB supports to delete a range of timeseries points. Users can write SQL
expressions as follows to specify the delete interval:
-
-```sql
-delete from root.ln.wf02.wt02.status where time < 10
-delete from root.ln.wf02.wt02.status where time <= 10
-delete from root.ln.wf02.wt02.status where time < 20 and time > 10
-delete from root.ln.wf02.wt02.status where time <= 20 and time >= 10
-delete from root.ln.wf02.wt02.status where time > 20
-delete from root.ln.wf02.wt02.status where time >= 20
-delete from root.ln.wf02.wt02.status where time = 20
-```
-
-Please pay attention that multiple intervals connected by "OR" expression are
not supported in delete statement:
-
-```
-delete from root.ln.wf02.wt02.status where time > 4 or time < 0
-Msg: 303: Check metadata error: For delete statement, where clause can only
contain atomic
-expressions like : time > XXX, time <= XXX, or two atomic expressions
connected by 'AND'
-```
-
-If no "where" clause specified in a delete statement, all the data in a
timeseries will be deleted.
-
-```sql
-delete from root.ln.wf02.wt02.status
-```
-
-
-## Delete Multiple Timeseries
-
-If both the power supply status and hardware version of the ln group wf02
plant wt02 device before 2017-11-01 16:26:00 need to be deleted, [the prefix
path with broader meaning or the path with
star](../Basic-Concept/Data-Model-and-Terminology.md) can be used to delete the
data. The SQL statement for this operation is:
-
-```sql
-delete from root.ln.wf02.wt02 where time <= 2017-11-01T16:26:00;
-```
-
-or
-
-```sql
-delete from root.ln.wf02.wt02.* where time <= 2017-11-01T16:26:00;
-```
-
-It should be noted that when the deleted path does not exist, IoTDB will not
prompt that the path does not exist, but that the execution is successful,
because SQL is a declarative programming method. Unless it is a syntax error,
insufficient permissions and so on, it is not considered an error, as shown
below:
-
-```
-IoTDB> delete from root.ln.wf03.wt02.status where time < now()
-Msg: The statement is executed successfully.
-```
-
-## Delete Time Partition (experimental)
-
-You may delete all data in a time partition of a database using the following
grammar:
-
-```sql
-DELETE PARTITION root.ln 0,1,2
-```
-
-The `0,1,2` above is the id of the partition that is to be deleted, you can
find it from the IoTDB
-data folders or convert a timestamp manually to an id using `timestamp /
partitionInterval
-` (flooring), and the `partitionInterval` should be in your config (if
time-partitioning is
-supported in your version).
-
-Please notice that this function is experimental and mainly for development,
please use it with care.
-
-## Time-to-live (TTL)
-
-IoTDB supports storage-level TTL settings, which means it is able to delete
old data automatically and periodically. The benefit of using TTL is that
hopefully you can control the total disk space usage and prevent the machine
from running out of disks. Moreover, the query performance may downgrade as the
total number of files goes up and the memory usage also increase as there are
more files. Timely removing such files helps to keep at a high query
performance level and reduce memory usage.
-
-The default unit of TTL is milliseconds. If the time precision in the
configuration file changes to another, the TTL is still set to milliseconds.
-
-### Set TTL
-
-The SQL Statement for setting TTL is as follow:
-
-```
-IoTDB> set ttl to root.ln 3600000
-```
-
-This example means that for data in `root.ln`, only 3600000 ms, that is, the
latest 1 hour will remain, the older one is removed or made invisible.
-
-```
-IoTDB> set ttl to root.sgcc.** 3600000
-```
-
-It supports setting TTL for databases in a path. This example represents
setting TTL for all databases in the `root.sgcc` path.
-
-```
-IoTDB> set ttl to root.** 3600000
-```
-
-This example represents setting TTL for all databases.
-
-### Unset TTL
-
-To unset TTL, we can use follwing SQL statement:
-
-```
-IoTDB> unset ttl to root.ln
-```
-
-After unset TTL, all data will be accepted in `root.ln`.
-
-```
-IoTDB> unset ttl to root.sgcc.**
-```
-
-Unset the TTL setting for all databases in the `root.sgcc` path.
-
-```
-IoTDB> unset ttl to root.**
-```
-
-Unset the TTL setting for all databases.
-
-### Show TTL
-
-To Show TTL, we can use following SQL statement:
-
-```
-IoTDB> SHOW ALL TTL
-IoTDB> SHOW TTL ON StorageGroupNames
-```
-
-The SHOW ALL TTL example gives the TTL for all databases.
-The SHOW TTL ON root.ln,root.sgcc,root.DB example shows the TTL for the three
storage
-groups specified.
-Note: the TTL for databases that do not have a TTL set will display as null.
-
-```
-IoTDB> show all ttl
-+----------+-------+
-| database|ttl(ms)|
-+---------+-------+
-| root.ln|3600000|
-|root.sgcc| null|
-| root.DB|3600000|
-+----------+-------+
-```
-
diff --git a/src/UserGuide/Master/User-Manual/Write-Delete-Data.md
b/src/UserGuide/Master/User-Manual/Write-Delete-Data.md
index 7f4fee2..cf23144 100644
--- a/src/UserGuide/Master/User-Manual/Write-Delete-Data.md
+++ b/src/UserGuide/Master/User-Manual/Write-Delete-Data.md
@@ -23,15 +23,15 @@
# Write & Delete Data
## CLI INSERT
-IoTDB provides users with a variety of ways to insert real-time data, such as
directly inputting [INSERT SQL statement](../Reference/SQL-Reference.md) in
[Client/Shell tools](../QuickStart/Command-Line-Interface.md), or using [Java
JDBC](../API/Programming-JDBC.md) to perform single or batch execution of
[INSERT SQL statement](../Reference/SQL-Reference.md).
+IoTDB provides users with a variety of ways to insert real-time data, such as
directly inputting [INSERT SQL
statement](../SQL-Manual/SQL-Manual.md#insert-data) in [Client/Shell
tools](../Tools-System/CLI.md), or using [Java
JDBC](../API/Programming-JDBC.md) to perform single or batch execution of
[INSERT SQL statement](../SQL-Manual/SQL-Manual.md).
-NOTE： This section mainly introduces the use of [INSERT SQL
statement](../Reference/SQL-Reference.md) for real-time data import in the
scenario.
+NOTE： This section mainly introduces the use of [INSERT SQL
statement](../SQL-Manual/SQL-Manual.md#insert-data) for real-time data import
in the scenario.
Writing a repeat timestamp covers the original timestamp data, which can be
regarded as updated data.
### Use of INSERT Statements
-The [INSERT SQL statement](../Reference/SQL-Reference.md) statement is used to
insert data into one or more specified timeseries created. For each point of
data inserted, it consists of a
[timestamp](../Basic-Concept/Data-Model-and-Terminology.md) and a sensor
acquisition value (see [Data Type](../Basic-Concept/Data-Type.md)).
+The [INSERT SQL statement](../SQL-Manual/SQL-Manual.md#insert-data) statement
is used to insert data into one or more specified timeseries created. For each
point of data inserted, it consists of a
[timestamp](../Basic-Concept/Data-Model-and-Terminology.md) and a sensor
acquisition value (see [Data Type](../Basic-Concept/Data-Type.md)).
In the scenario of this section, take two timeseries
`root.ln.wf02.wt02.status` and `root.ln.wf02.wt02.hardware` as an example, and
their data types are BOOLEAN and TEXT, respectively.
@@ -193,7 +193,7 @@ CSV stores table data in plain text. You can write multiple
formatted data into
## DELETE
-Users can delete data that meet the deletion condition in the specified
timeseries by using the [DELETE statement](../Reference/SQL-Reference.md). When
deleting data, users can select one or more timeseries paths, prefix paths, or
paths with star to delete data within a certain time interval.
+Users can delete data that meet the deletion condition in the specified
timeseries by using the [DELETE
statement](../SQL-Manual/SQL-Manual.md#delete-data). When deleting data, users
can select one or more timeseries paths, prefix paths, or paths with star to
delete data within a certain time interval.
In a JAVA programming environment, you can use the [Java
JDBC](../API/Programming-JDBC.md) to execute single or batch UPDATE statements.
diff --git
a/src/UserGuide/latest/Deployment-and-Maintenance/Security-Management.md
b/src/UserGuide/latest/Deployment-and-Maintenance/Security-Management.md
index bdb3d4b..7c873b6 100644
--- a/src/UserGuide/latest/Deployment-and-Maintenance/Security-Management.md
+++ b/src/UserGuide/latest/Deployment-and-Maintenance/Security-Management.md
@@ -25,7 +25,7 @@
IoTDB provides users with account privilege management operations, so as to
ensure data security.
-We will show you basic user privilege management operations through the
following specific examples. Detailed SQL syntax and usage details can be found
in [SQL Documentation](../Reference/SQL-Reference.md).
+We will show you basic user privilege management operations through the
following specific examples. Detailed SQL syntax and usage details can be found
in [SQL Documentation](../SQL-Manual/SQL-Manual.md).
At the same time, in the JAVA programming environment, you can use the [Java
JDBC](../API/Programming-JDBC.md) to execute privilege management statements in
a single or batch mode.
### Basic Concepts
@@ -372,7 +372,7 @@ At the same time, changes to roles are immediately
reflected on all users who ow
| CREATE\_TIMESERIES | create timeseries; path dependent
|
Eg1: create timeseries<br />`create timeseries root.ln.wf02.status with
datatype=BOOLEAN,encoding=PLAIN;`<br />Eg2: create aligned timeseries<br
/>`create aligned timeseries root.ln.device1(latitude FLOAT encoding=PLAIN
compressor=SNAPPY, longitude FLOAT encoding=PLAIN compressor=SNAPPY);`
[...]
| INSERT\_TIMESERIES | insert data; path dependent
|
Eg1: `insert into root.ln.wf02(timestamp,status) values(1,true);`<br />Eg2:
`insert into root.sg1.d1(time, s1, s2) aligned values(1, 1, 1)`
[...]
| ALTER\_TIMESERIES | alter timeseries; path dependent
|
Eg1: `alter timeseries root.turbine.d1.s1 ADD TAGS tag3=v3, tag4=v4;`<br />Eg2:
`ALTER timeseries root.turbine.d1.s1 UPSERT ALIAS=newAlias TAGS(tag2=newV2,
tag3=v3) ATTRIBUTES(attr3=v3, attr4=v4);`
[...]
-| READ\_TIMESERIES | query data; path dependent
|
Eg1: `SHOW DATABASES;` <br />Eg2: `show child paths root.ln, show child nodes
root.ln;`<br />Eg3: `show devices;`<br />Eg4: `show timeseries root.**;`<br
/>Eg5: `show schema templates;`<br />Eg6: `show all ttl`<br />Eg7:
[Query-Data](../Query-Data/Overview.md)（The query statements under this section
all use this permission）<br />Eg [...]
+| READ\_TIMESERIES | query data; path dependent
|
Eg1: `SHOW DATABASES;` <br />Eg2: `show child paths root.ln, show child nodes
root.ln;`<br />Eg3: `show devices;`<br />Eg4: `show timeseries root.**;`<br
/>Eg5: `show schema templates;`<br />Eg6: `show all ttl`<br />Eg7:
[Query-Data](../User-Manual/Query-Data.md)（The query statements under this
section all use this permission）<br / [...]
| DELETE\_TIMESERIES | delete data or timeseries; path dependent
|
Eg1: delete timeseries<br />`delete timeseries root.ln.wf01.wt01.status`<br
/>Eg2: delete data<br />`delete from root.ln.wf02.wt02.status where time <
10`<br />Eg3: use drop semantic<br />`drop timeseries root.ln.wf01.wt01.status
[...]
| CREATE\_USER | create users; path independent
|
Eg: `create user thulab 'passwd';`
[...]
| DELETE\_USER | delete users; path independent
|
Eg: `drop user xiaoming;`
[...]
diff --git
a/src/UserGuide/latest/Deployment-and-Maintenance/Security-Management_timecho.md
b/src/UserGuide/latest/Deployment-and-Maintenance/Security-Management_timecho.md
index 9bb3593..13e25b0 100644
---
a/src/UserGuide/latest/Deployment-and-Maintenance/Security-Management_timecho.md
+++
b/src/UserGuide/latest/Deployment-and-Maintenance/Security-Management_timecho.md
@@ -33,7 +33,7 @@ TODO
IoTDB provides users with account privilege management operations, so as to
ensure data security.
-We will show you basic user privilege management operations through the
following specific examples. Detailed SQL syntax and usage details can be found
in [SQL Documentation](../Reference/SQL-Reference.md).
+We will show you basic user privilege management operations through the
following specific examples. Detailed SQL syntax and usage details can be found
in [SQL Documentation](../SQL-Manual/SQL-Manual.md).
At the same time, in the JAVA programming environment, you can use the [Java
JDBC](../API/Programming-JDBC.md) to execute privilege management statements in
a single or batch mode.
### Basic Concepts
@@ -380,7 +380,7 @@ At the same time, changes to roles are immediately
reflected on all users who ow
| CREATE\_TIMESERIES | create timeseries; path dependent
|
Eg1: create timeseries<br />`create timeseries root.ln.wf02.status with
datatype=BOOLEAN,encoding=PLAIN;`<br />Eg2: create aligned timeseries<br
/>`create aligned timeseries root.ln.device1(latitude FLOAT encoding=PLAIN
compressor=SNAPPY, longitude FLOAT encoding=PLAIN compressor=SNAPPY);`
[...]
| INSERT\_TIMESERIES | insert data; path dependent
|
Eg1: `insert into root.ln.wf02(timestamp,status) values(1,true);`<br />Eg2:
`insert into root.sg1.d1(time, s1, s2) aligned values(1, 1, 1)`
[...]
| ALTER\_TIMESERIES | alter timeseries; path dependent
|
Eg1: `alter timeseries root.turbine.d1.s1 ADD TAGS tag3=v3, tag4=v4;`<br />Eg2:
`ALTER timeseries root.turbine.d1.s1 UPSERT ALIAS=newAlias TAGS(tag2=newV2,
tag3=v3) ATTRIBUTES(attr3=v3, attr4=v4);`
[...]
-| READ\_TIMESERIES | query data; path dependent
|
Eg1: `SHOW DATABASES;` <br />Eg2: `show child paths root.ln, show child nodes
root.ln;`<br />Eg3: `show devices;`<br />Eg4: `show timeseries root.**;`<br
/>Eg5: `show schema templates;`<br />Eg6: `show all ttl`<br />Eg7:
[Query-Data](../Query-Data/Overview.md)（The query statements under this section
all use this permission）<br />Eg [...]
+| READ\_TIMESERIES | query data; path dependent
|
Eg1: `SHOW DATABASES;` <br />Eg2: `show child paths root.ln, show child nodes
root.ln;`<br />Eg3: `show devices;`<br />Eg4: `show timeseries root.**;`<br
/>Eg5: `show schema templates;`<br />Eg6: `show all ttl`<br />Eg7:
[Query-Data](../User-Manual/Query-Data.md)（The query statements under this
section all use this permission）<br / [...]
| DELETE\_TIMESERIES | delete data or timeseries; path dependent
|
Eg1: delete timeseries<br />`delete timeseries root.ln.wf01.wt01.status`<br
/>Eg2: delete data<br />`delete from root.ln.wf02.wt02.status where time <
10`<br />Eg3: use drop semantic<br />`drop timeseries root.ln.wf01.wt01.status
[...]
| CREATE\_USER | create users; path independent
|
Eg: `create user thulab 'passwd';`
[...]
| DELETE\_USER | delete users; path independent
|
Eg: `drop user xiaoming;`
[...]
diff --git a/src/UserGuide/latest/Reference/UDF-Libraries.md
b/src/UserGuide/latest/Reference/UDF-Libraries.md
index 9eadaba..26efdb6 100644
--- a/src/UserGuide/latest/Reference/UDF-Libraries.md
+++ b/src/UserGuide/latest/Reference/UDF-Libraries.md
@@ -604,14 +604,14 @@ Output series:
This function is used to calculate the auto-correlation factor of the input
time series,
which equals to cross correlation between the same series.
-For more information, please refer to [XCorr](./Data-Matching.md#XCorr)
function.
+For more information, please refer to [XCorr](./UDF-Libraries.md#xcorr)
function.
**Name:** ACF
**Input Series:** Only support a single input numeric series. The type is
INT32 / INT64 / FLOAT / DOUBLE.
**Output Series:** Output a single series. The type is DOUBLE.
-There are $2N-1$ data points in the series, and the values are interpreted in
details in [XCorr](./Data-Matching.md#XCorr) function.
+There are $2N-1$ data points in the series, and the values are interpreted in
details in [XCorr](./UDF-Libraries.md#XCorr) function.
**Note:**
diff --git a/src/UserGuide/latest/SQL-Manual/SQL-Manual.md
b/src/UserGuide/latest/SQL-Manual/SQL-Manual.md
index 8259362..8d3f4d0 100644
--- a/src/UserGuide/latest/SQL-Manual/SQL-Manual.md
+++ b/src/UserGuide/latest/SQL-Manual/SQL-Manual.md
@@ -1088,11 +1088,11 @@ select change_points(s1), change_points(s2),
change_points(s3), change_points(s4
## DATA QUALITY FUNCTION LIBRARY
-For more details, see document
[Operator-and-Expression](../Reference/Function-and-Expression.md).
+For more details, see document
[Operator-and-Expression](../Reference/UDF-Libraries.md#).
### Data Quality
-For details and examples, see the document
[Data-Quality](../Operators-Functions/Data-Quality.md).
+For details and examples, see the document
[Data-Quality](../Reference/UDF-Libraries.md#data-quality).
```sql
# Completeness
@@ -1117,7 +1117,7 @@ select Accuracy(t1,t2,t3,m1,m2,m3) from root.test
### Data Profiling
-For details and examples, see the document
[Data-Profiling](../Operators-Functions/Data-Profiling.md).
+For details and examples, see the document
[Data-Profiling](../Reference/UDF-Libraries.md#data-profiling).
```sql
# ACF
@@ -1197,7 +1197,7 @@ select zscore(s1) from root.test
### Anomaly Detection
-For details and examples, see the document
[Anomaly-Detection](../Operators-Functions/Anomaly-Detection.md).
+For details and examples, see the document
[Anomaly-Detection](../Reference/UDF-Libraries.md#anomaly-detection).
```sql
# IQR
@@ -1232,7 +1232,7 @@ select
MasterDetect(lo,la,m_lo,m_la,model,'output_type'='anomaly','p'='3','k'='3
### Frequency Domain
-For details and examples, see the document
[Frequency-Domain](../Operators-Functions/Frequency-Domain.md).
+For details and examples, see the document
[Frequency-Domain](../Reference/UDF-Libraries.md#frequency-domain-analysis).
```sql
# Conv
@@ -1261,7 +1261,7 @@ select lowpass(s1,'wpass'='0.45') from root.test.d1
### Data Matching
-For details and examples, see the document
[Data-Matching](../Operators-Functions/Data-Matching.md).
+For details and examples, see the document
[Data-Matching](../Reference/UDF-Libraries.md#data-matching).
```sql
# Cov
@@ -1282,7 +1282,7 @@ select xcorr(s1, s2) from root.test.d1 where time <=
2020-01-01 00:00:05
### Data Repairing
-For details and examples, see the document
[Data-Repairing](../Operators-Functions/Data-Repairing.md).
+For details and examples, see the document
[Data-Repairing](../Reference/UDF-Libraries.md#data-repairing).
```sql
# TimestampRepair
@@ -1307,7 +1307,7 @@ select seasonalrepair(s1,'method'='improved','period'=3)
from root.test.d2
### Series Discovery
-For details and examples, see the document
[Series-Discovery](../Operators-Functions/Series-Discovery.md).
+For details and examples, see the document
[Series-Discovery](../Reference/UDF-Libraries.md#series-discovery).
```sql
# ConsecutiveSequences
@@ -1320,7 +1320,7 @@ select consecutivewindows(s1,s2,'length'='10m') from
root.test.d1
### Machine Learning
-For details and examples, see the document
[Machine-Learning](../Operators-Functions/Machine-Learning.md).
+For details and examples, see the document
[Machine-Learning](../Reference/UDF-Libraries.md#machine-learning).
```sql
# AR
@@ -1335,7 +1335,7 @@ select rm(s0, s1,"tb"="3","vb"="2") from root.test.d0
## LAMBDA EXPRESSION
-For details and examples, see the document
[Lambda](../Operators-Functions/Lambda.md).
+For details and examples, see the document
[Lambda](../Reference/Function-and-Expression#lambda-expression).
```sql
select jexl(temperature, 'expr'='x -> {x + x}') as jexl1, jexl(temperature,
'expr'='x -> {x * 3}') as jexl2, jexl(temperature, 'expr'='x -> {x * x}') as
jexl3, jexl(temperature, 'expr'='x -> {multiply(x, 100)}') as jexl4,
jexl(temperature, st, 'expr'='(x, y) -> {x + y}') as jexl5, jexl(temperature,
st, str, 'expr'='(x, y, z) -> {x + y + z}') as jexl6 from root.ln.wf01.wt01;```
@@ -1343,7 +1343,7 @@ select jexl(temperature, 'expr'='x -> {x + x}') as jexl1,
jexl(temperature, 'exp
## CONDITIONAL EXPRESSION
-For details and examples, see the document [Conditional
Expressions](../Operators-Functions/Conditional.md).
+For details and examples, see the document [Conditional
Expressions](../Reference/Function-and-Expression#conditional-expressions).
```sql
select T, P, case
@@ -1543,7 +1543,7 @@ CQs can't be altered once they're created. To change a
CQ, you must `DROP` and r
## USER-DEFINED FUNCTION (UDF)
-For more details, see document
[Operator-and-Expression](../User-Manual/Operator-and-Expression.md).
+For more details, see document
[Operator-and-Expression](../Reference/UDF-Libraries.md).
### UDF Registration
diff --git a/src/UserGuide/latest/User-Manual/Database-Programming.md
b/src/UserGuide/latest/User-Manual/Database-Programming.md
index 98c91aa..687247a 100644
--- a/src/UserGuide/latest/User-Manual/Database-Programming.md
+++ b/src/UserGuide/latest/User-Manual/Database-Programming.md
@@ -1873,17 +1873,17 @@ When you have prepared the UDF source code, test cases,
and instructions, you ar
#### Built-in UDF
-1. Aggregate Functions, such as `SUM`. For details and examples, see the
document [Aggregate Functions](../Operators-Functions/Aggregation.md).
-2. Arithmetic Functions, such as `SIN`. For details and examples, see the
document [Arithmetic Operators and
Functions](../Operators-Functions/Mathematical.md).
-3. Comparison Functions, such as `ON_OFF`. For details and examples, see the
document [Comparison Operators and
Functions](../Operators-Functions/Comparison.md).
-4. String Processing Functions, such as `STRING_CONTAINS`. For details and
examples, see the document [String
Processing](../Operators-Functions/String.md).
-5. Data Type Conversion Function, such as `CAST`. For details and examples,
see the document [Data Type Conversion
Function](../Operators-Functions/Conversion.md).
-6. Constant Timeseries Generating Functions, such as `CONST`. For details
and examples, see the document [Constant Timeseries Generating
Functions](../Operators-Functions/Constant.md).
-7. Selector Functions, such as `TOP_K`. For details and examples, see the
document [Selector Functions](../Operators-Functions/Selection.md).
-8. Continuous Interval Functions, such as `ZERO_DURATION`. For details and
examples, see the document [Continuous Interval
Functions](../Operators-Functions/Continuous-Interval.md).
-9. Variation Trend Calculation Functions, such as `TIME_DIFFERENCE`. For
details and examples, see the document [Variation Trend Calculation
Functions](../Operators-Functions/Variation-Trend.md).
-10. Sample Functions, such as `M4`. For details and examples, see the
document [Sample Functions](../Operators-Functions/Sample.md).
-11. Change Points Function, such as `CHANGE_POINTS`. For details and
examples, see the document [Time-Series](../Operators-Functions/Time-Series.md).
+1. Aggregate Functions, such as `SUM`. For details and examples, see the
document [Aggregate
Functions](../Reference/Function-and-Expression.md#aggregate-functions).
+2. Arithmetic Functions, such as `SIN`. For details and examples, see the
document [Arithmetic Operators and
Functions](../Reference/Function-and-Expression.md#arithmetic-operators-and-functions).
+3. Comparison Functions, such as `ON_OFF`. For details and examples, see the
document [Comparison Operators and
Functions](../Reference/Function-and-Expression.md#comparison-operators-and-functions).
+4. String Processing Functions, such as `STRING_CONTAINS`. For details and
examples, see the document [String
Processing](../Reference/Function-and-Expression.md#string-processing).
+5. Data Type Conversion Function, such as `CAST`. For details and examples,
see the document [Data Type Conversion
Function](../Reference/Function-and-Expression.md#data-type-conversion-function).
+6. Constant Timeseries Generating Functions, such as `CONST`. For details
and examples, see the document [Constant Timeseries Generating
Functions](../Reference/Function-and-Expression.md#constant-timeseries-generating-functions).
+7. Selector Functions, such as `TOP_K`. For details and examples, see the
document [Selector
Functions](../Reference/Function-and-Expression.md#selector-functions).
+8. Continuous Interval Functions, such as `ZERO_DURATION`. For details and
examples, see the document [Continuous Interval
Functions](../Reference/Function-and-Expression.md#continuous-interval-functions).
+9. Variation Trend Calculation Functions, such as `TIME_DIFFERENCE`. For
details and examples, see the document [Variation Trend Calculation
Functions](../Reference/Function-and-Expression.md#variation-trend-calculation-functions).
+10. Sample Functions, such as `M4`. For details and examples, see the
document [Sample
Functions](../Reference/Function-and-Expression.md#sample-functions).
+11. Change Points Function, such as `CHANGE_POINTS`. For details and
examples, see the document
[Time-Series](../Reference/Function-and-Expression.md#time-series-processing).
#### Data Quality Function Library
@@ -1902,14 +1902,14 @@ The functions in this function library are not built-in
functions, and must be l
##### Implemented Functions
-1. Data Quality related functions, such as `Completeness`. For details and
examples, see the document
[Data-Quality](../Operators-Functions/Data-Quality.md).
-2. Data Profiling related functions, such as `ACF`. For details and
examples, see the document
[Data-Profiling](../Operators-Functions/Data-Profiling.md).
-3. Anomaly Detection related functions, such as `IQR`. For details and
examples, see the document
[Anomaly-Detection](../Operators-Functions/Anomaly-Detection.md).
-4. Frequency Domain Analysis related functions, such as `Conv`. For details
and examples, see the document
[Frequency-Domain](../Operators-Functions/Frequency-Domain.md).
-5. Data Matching related functions, such as `DTW`. For details and examples,
see the document [Data-Matching](../Operators-Functions/Data-Matching.md).
-6. Data Repairing related functions, such as `TimestampRepair`. For details
and examples, see the document
[Data-Repairing](../Operators-Functions/Data-Repairing.md).
-7. Series Discovery related functions, such as `ConsecutiveSequences`. For
details and examples, see the document
[Series-Discovery](../Operators-Functions/Series-Discovery.md).
-8. Machine Learning related functions, such as `AR`. For details and
examples, see the document
[Machine-Learning](../Operators-Functions/Machine-Learning.md).
+1. Data Quality related functions, such as `Completeness`. For details and
examples, see the document
[Data-Quality](../Reference/UDF-Libraries.md#data-quality).
+2. Data Profiling related functions, such as `ACF`. For details and
examples, see the document
[Data-Profiling](../Reference/UDF-Libraries.md#data-profiling).
+3. Anomaly Detection related functions, such as `IQR`. For details and
examples, see the document
[Anomaly-Detection](../Reference/UDF-Libraries.md#anomaly-detection).
+4. Frequency Domain Analysis related functions, such as `Conv`. For details
and examples, see the document
[Frequency-Domain](../Reference/UDF-Libraries.md#frequency-domain-analysis).
+5. Data Matching related functions, such as `DTW`. For details and examples,
see the document [Data-Matching](../Reference/UDF-Libraries.md#data-matching).
+6. Data Repairing related functions, such as `TimestampRepair`. For details
and examples, see the document
[Data-Repairing](../Reference/UDF-Libraries.md#data-repairing).
+7. Series Discovery related functions, such as `ConsecutiveSequences`. For
details and examples, see the document
[Series-Discovery](../Reference/UDF-Libraries.md#series-discovery).
+8. Machine Learning related functions, such as `AR`. For details and
examples, see the document
[Machine-Learning](../Reference/UDF-Libraries.md#machine-learning).
### Q&A
diff --git a/src/UserGuide/latest/User-Manual/Delete-Data.md
b/src/UserGuide/latest/User-Manual/Delete-Data.md
deleted file mode 100644
index 05d3ad1..0000000
--- a/src/UserGuide/latest/User-Manual/Delete-Data.md
+++ /dev/null
@@ -1,181 +0,0 @@
-<!--
-
- Licensed to the Apache Software Foundation (ASF) under one
- or more contributor license agreements. See the NOTICE file
- distributed with this work for additional information
- regarding copyright ownership. The ASF licenses this file
- to you under the Apache License, Version 2.0 (the
- "License"); you may not use this file except in compliance
- with the License. You may obtain a copy of the License at
-
- http://www.apache.org/licenses/LICENSE-2.0
-
- Unless required by applicable law or agreed to in writing,
- software distributed under the License is distributed on an
- "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
- KIND, either express or implied. See the License for the
- specific language governing permissions and limitations
- under the License.
-
--->
-
-# DELETE
-
-Users can delete data that meet the deletion condition in the specified
timeseries by using the [DELETE statement](../Reference/SQL-Reference.md). When
deleting data, users can select one or more timeseries paths, prefix paths, or
paths with star to delete data within a certain time interval.
-
-In a JAVA programming environment, you can use the [Java
JDBC](../API/Programming-JDBC.md) to execute single or batch UPDATE statements.
-
-## Delete Single Timeseries
-
-Taking ln Group as an example, there exists such a usage scenario:
-
-The wf02 plant's wt02 device has many segments of errors in its power supply
status before 2017-11-01 16:26:00, and the data cannot be analyzed correctly.
The erroneous data affected the correlation analysis with other devices. At
this point, the data before this time point needs to be deleted. The SQL
statement for this operation is
-
-```sql
-delete from root.ln.wf02.wt02.status where time<=2017-11-01T16:26:00;
-```
-
-In case we hope to merely delete the data before 2017-11-01 16:26:00 in the
year of 2017, The SQL statement is:
-
-```sql
-delete from root.ln.wf02.wt02.status where time>=2017-01-01T00:00:00 and
time<=2017-11-01T16:26:00;
-```
-
-IoTDB supports to delete a range of timeseries points. Users can write SQL
expressions as follows to specify the delete interval:
-
-```sql
-delete from root.ln.wf02.wt02.status where time < 10
-delete from root.ln.wf02.wt02.status where time <= 10
-delete from root.ln.wf02.wt02.status where time < 20 and time > 10
-delete from root.ln.wf02.wt02.status where time <= 20 and time >= 10
-delete from root.ln.wf02.wt02.status where time > 20
-delete from root.ln.wf02.wt02.status where time >= 20
-delete from root.ln.wf02.wt02.status where time = 20
-```
-
-Please pay attention that multiple intervals connected by "OR" expression are
not supported in delete statement:
-
-```
-delete from root.ln.wf02.wt02.status where time > 4 or time < 0
-Msg: 303: Check metadata error: For delete statement, where clause can only
contain atomic
-expressions like : time > XXX, time <= XXX, or two atomic expressions
connected by 'AND'
-```
-
-If no "where" clause specified in a delete statement, all the data in a
timeseries will be deleted.
-
-```sql
-delete from root.ln.wf02.wt02.status
-```
-
-
-## Delete Multiple Timeseries
-
-If both the power supply status and hardware version of the ln group wf02
plant wt02 device before 2017-11-01 16:26:00 need to be deleted, [the prefix
path with broader meaning or the path with
star](../Basic-Concept/Data-Model-and-Terminology.md) can be used to delete the
data. The SQL statement for this operation is:
-
-```sql
-delete from root.ln.wf02.wt02 where time <= 2017-11-01T16:26:00;
-```
-
-or
-
-```sql
-delete from root.ln.wf02.wt02.* where time <= 2017-11-01T16:26:00;
-```
-
-It should be noted that when the deleted path does not exist, IoTDB will not
prompt that the path does not exist, but that the execution is successful,
because SQL is a declarative programming method. Unless it is a syntax error,
insufficient permissions and so on, it is not considered an error, as shown
below:
-
-```
-IoTDB> delete from root.ln.wf03.wt02.status where time < now()
-Msg: The statement is executed successfully.
-```
-
-## Delete Time Partition (experimental)
-
-You may delete all data in a time partition of a database using the following
grammar:
-
-```sql
-DELETE PARTITION root.ln 0,1,2
-```
-
-The `0,1,2` above is the id of the partition that is to be deleted, you can
find it from the IoTDB
-data folders or convert a timestamp manually to an id using `timestamp /
partitionInterval
-` (flooring), and the `partitionInterval` should be in your config (if
time-partitioning is
-supported in your version).
-
-Please notice that this function is experimental and mainly for development,
please use it with care.
-
-## Time-to-live (TTL)
-
-IoTDB supports storage-level TTL settings, which means it is able to delete
old data automatically and periodically. The benefit of using TTL is that
hopefully you can control the total disk space usage and prevent the machine
from running out of disks. Moreover, the query performance may downgrade as the
total number of files goes up and the memory usage also increase as there are
more files. Timely removing such files helps to keep at a high query
performance level and reduce memory usage.
-
-The default unit of TTL is milliseconds. If the time precision in the
configuration file changes to another, the TTL is still set to milliseconds.
-
-### Set TTL
-
-The SQL Statement for setting TTL is as follow:
-
-```
-IoTDB> set ttl to root.ln 3600000
-```
-
-This example means that for data in `root.ln`, only 3600000 ms, that is, the
latest 1 hour will remain, the older one is removed or made invisible.
-
-```
-IoTDB> set ttl to root.sgcc.** 3600000
-```
-
-It supports setting TTL for databases in a path. This example represents
setting TTL for all databases in the `root.sgcc` path.
-
-```
-IoTDB> set ttl to root.** 3600000
-```
-
-This example represents setting TTL for all databases.
-
-### Unset TTL
-
-To unset TTL, we can use follwing SQL statement:
-
-```
-IoTDB> unset ttl to root.ln
-```
-
-After unset TTL, all data will be accepted in `root.ln`.
-
-```
-IoTDB> unset ttl to root.sgcc.**
-```
-
-Unset the TTL setting for all databases in the `root.sgcc` path.
-
-```
-IoTDB> unset ttl to root.**
-```
-
-Unset the TTL setting for all databases.
-
-### Show TTL
-
-To Show TTL, we can use following SQL statement:
-
-```
-IoTDB> SHOW ALL TTL
-IoTDB> SHOW TTL ON StorageGroupNames
-```
-
-The SHOW ALL TTL example gives the TTL for all databases.
-The SHOW TTL ON root.ln,root.sgcc,root.DB example shows the TTL for the three
storage
-groups specified.
-Note: the TTL for databases that do not have a TTL set will display as null.
-
-```
-IoTDB> show all ttl
-+----------+-------+
-| database|ttl(ms)|
-+---------+-------+
-| root.ln|3600000|
-|root.sgcc| null|
-| root.DB|3600000|
-+----------+-------+
-```
-
diff --git a/src/UserGuide/latest/User-Manual/Write-Delete-Data.md
b/src/UserGuide/latest/User-Manual/Write-Delete-Data.md
index 7f4fee2..cf23144 100644
--- a/src/UserGuide/latest/User-Manual/Write-Delete-Data.md
+++ b/src/UserGuide/latest/User-Manual/Write-Delete-Data.md
@@ -23,15 +23,15 @@
# Write & Delete Data
## CLI INSERT
-IoTDB provides users with a variety of ways to insert real-time data, such as
directly inputting [INSERT SQL statement](../Reference/SQL-Reference.md) in
[Client/Shell tools](../QuickStart/Command-Line-Interface.md), or using [Java
JDBC](../API/Programming-JDBC.md) to perform single or batch execution of
[INSERT SQL statement](../Reference/SQL-Reference.md).
+IoTDB provides users with a variety of ways to insert real-time data, such as
directly inputting [INSERT SQL
statement](../SQL-Manual/SQL-Manual.md#insert-data) in [Client/Shell
tools](../Tools-System/CLI.md), or using [Java
JDBC](../API/Programming-JDBC.md) to perform single or batch execution of
[INSERT SQL statement](../SQL-Manual/SQL-Manual.md).
-NOTE： This section mainly introduces the use of [INSERT SQL
statement](../Reference/SQL-Reference.md) for real-time data import in the
scenario.
+NOTE： This section mainly introduces the use of [INSERT SQL
statement](../SQL-Manual/SQL-Manual.md#insert-data) for real-time data import
in the scenario.
Writing a repeat timestamp covers the original timestamp data, which can be
regarded as updated data.
### Use of INSERT Statements
-The [INSERT SQL statement](../Reference/SQL-Reference.md) statement is used to
insert data into one or more specified timeseries created. For each point of
data inserted, it consists of a
[timestamp](../Basic-Concept/Data-Model-and-Terminology.md) and a sensor
acquisition value (see [Data Type](../Basic-Concept/Data-Type.md)).
+The [INSERT SQL statement](../SQL-Manual/SQL-Manual.md#insert-data) statement
is used to insert data into one or more specified timeseries created. For each
point of data inserted, it consists of a
[timestamp](../Basic-Concept/Data-Model-and-Terminology.md) and a sensor
acquisition value (see [Data Type](../Basic-Concept/Data-Type.md)).
In the scenario of this section, take two timeseries
`root.ln.wf02.wt02.status` and `root.ln.wf02.wt02.hardware` as an example, and
their data types are BOOLEAN and TEXT, respectively.
@@ -193,7 +193,7 @@ CSV stores table data in plain text. You can write multiple
formatted data into
## DELETE
-Users can delete data that meet the deletion condition in the specified
timeseries by using the [DELETE statement](../Reference/SQL-Reference.md). When
deleting data, users can select one or more timeseries paths, prefix paths, or
paths with star to delete data within a certain time interval.
+Users can delete data that meet the deletion condition in the specified
timeseries by using the [DELETE
statement](../SQL-Manual/SQL-Manual.md#delete-data). When deleting data, users
can select one or more timeseries paths, prefix paths, or paths with star to
delete data within a certain time interval.
In a JAVA programming environment, you can use the [Java
JDBC](../API/Programming-JDBC.md) to execute single or batch UPDATE statements.
diff --git a/src/zh/Download/README.md b/src/zh/Download/README.md
index ab1cd87..d06a074 100644
--- a/src/zh/Download/README.md
+++ b/src/zh/Download/README.md
@@ -224,7 +224,7 @@ insert into root.sg(time, a) values(4, "\u96d5")
* 停掉旧版本进程，启动新版本即可。
- 如何从 v0.13.x 升级到 v1.0.x？
- * 0.13版本与1.0版本的文件目录结构不同，**<font
color=red>不能将0.13的data目录直接拷贝到1.0集群使用</font>**。如果需要将0.13的数据导入至1.0，可以使用[LOAD](../UserGuide/Maintenance-Tools/Load-Tsfile.md)功能;
+ * 0.13版本与1.0版本的文件目录结构不同，**<font
color=red>不能将0.13的data目录直接拷贝到1.0集群使用</font>**。如果需要将0.13的数据导入至1.0，可以使用[LOAD](../UserGuide/Master/Tools-System/Import-Export-Tool.md)功能;
* __0.13版本的默认RPC地址是0.0.0.0，1.0版本的默认RPC地址是127.0.0.1__
- 如何从 v1.0.0 升级到 v1.x.0？
