API
内置模块和功能
我们提供了大量的内置函数供用户使用。下面是一个内置函数的列表。只要在脚本开头写上 import greptime 或 from greptime import * 就可以调用它们。
向量函数
| Function | Description |
|---|---|
pow(v0, v1) | Raise a number v0 to a power of v1. |
clip(v0, v1, v2) | Clip all elements in a vector v0 to a range between vectors v1 and v2. |
diff(v0) | Calculate the difference between adjacent elements in a vector v0. |
mean(v0) | Calculate the mean of a vector v0. |
polyval(v0, v1) | Evaluate a polynomial v0 at points v1. similar to numpy.polyval. |
argmax(v0) | Return the index of the maximum value in a vector v0. similar to numpy.argmax. |
argmin(v0) | Return the index of the minimum value in a vector v0. similar to numpy.argmin. |
percentile | Calculate the q-th percentile of a vector v0. similar to numpy.percentile. |
scipy_stats_norm_cdf | Calculate the cumulative distribution function for the normal distribution. similar to scipy.stats.norm.cdf. |
scipy_stats_norm_pdf | Calculate the probability density function for the normal distribution. similar to scipy.stats.norm.pdf. |
数学函数
| Function | Description |
|---|---|
sqrt(v) | Calculate the square root of a number v. |
sin(v) | Calculate the sine of a number v. |
cos(v) | Calculate the cosine of a number v. |
tan(v) | Calculate the tangent of a number v. |
asin(v) | Calculate the arcsine of a number v. |
acos(v) | Calculate the arccosine of a number v. |
atan(v) | Calculate the arctangent of a number v. |
floor(v) | Calculate the floor of a number v. |
ceil(v) | Calculate the ceiling of a number v. |
round(v) | Calculate the nearest integer of a number v. |
trunc(v) | Calculate the truncated integer of a number v. |
abs(v) | Calculate the absolute value of a number v. |
signum(v) | Calculate the sign(gives 1.0/-1.0) of a number v. |
exp(v) | Calculate the exponential of a number v. |
ln(v) | Calculate the natural logarithm of a number v. |
log2(v) | Calculate the base-2 logarithm of a number v. |
log10(v) | Calculate the base-10 logarithm of a number v. |
效用函数和聚合函数
这些函数是由 DataFusion 绑定的。
| Function | Description |
|---|---|
random(len) | Generate a random vector with length len. |
approx_distinct(v0) | Calculate the approximate number of distinct values in a vector v0. |
median(v0) | Calculate the median of a vector v0. |
approx_percentile_cont(values, percent) | Calculate the approximate percentile of a vector values at a given percentage percent. |
array_agg(v0) | Aggregate values into an array. |
avg(v0) | Calculate the average of a vector v0. |
correlation(v0, v1) | Calculate the Pearson correlation coefficient of a vector v0 and a vector v1. |
count(v0) | Calculate the count of a vector v0. |
covariance(v0, v1) | Calculate the covariance of a vector v0 and a vector v1. |
covariance_pop(v0, v1) | Calculate the population covariance of a vector v0 and a vector v1. |
max(v0) | Calculate the maximum of a vector v0. |
min(v0) | Calculate the minimum of a vector v0. |
stddev(v0) | Calculate the sample standard deviation of a vector v0. |
stddev_pop(v0) | Calculate the population standard deviation of a vector v0. |
sum(v0) | Calculate the sum of a vector v0. |
variance(v0) | Calculate the sample variance of a vector v0. |
variance_pop(v0) | Calculate the population variance of a vector v0. |
数据框架的 methods
| Method | Description |
|---|---|
select_columns(columns: List[str]) | select columns from DataFrame |
select(columns: List[Expr]]) | select columns from DataFrame using PyExpr |
filter(condition: Expr) | filter DataFrame using PyExpr |
aggregate(group_expr: List[Expr], aggr_expr: List[Expr]) | Perform an aggregate query with optional grouping expressions. |
limit(skip: int, fetch: Optional[int]) | Limit the number of rows returned from this DataFrame. skip - Number of rows to skip before fetch any row; fetch - Maximum number of rows to fetch, after skipping skip rows. |
union(other: DataFrame) | Union two DataFrame |
union_distinct(other: DataFrame) | Union two DataFrame, but remove duplicate rows |
distinct() | Remove duplicate rows |
sort(expr: List[Expr]) | Sort DataFrame by PyExpr, Sort the DataFrame by the specified sorting expressions. Any expression can be turned into a sort expression by calling its sort method. |
join(right: DataFrame, left_cols: List[str], right_cols: List[str], filter: Optional[Expr]) | Join two DataFrame using the specified columns as join keys. Eight Join Types are supported: inner, left, right, full, leftSemi, leftAnti, rightSemi, rightAnti. |
intersect(other: DataFrame) | Intersect two DataFrame |
except(other: DataFrame) | Except two DataFrame |
collect() | Collect DataFrame to a list of PyVector |
Expr 的 methods
| Method | Description |
|---|---|
col(name: str) | Create a PyExpr that represents a column |
lit(value: Any) | Create a PyExpr that represents a literal value |
sort(ascending: bool, null_first: bool) | Create a PyExpr that represents a sort expression |
comparison operators: ==, !=, >, >=, <, <= | Create PyExpr from compare two PyExpr |
logical operators: &, |, ~ | Create PyExpr from logical operation between two PyExpr |