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Builtin modules and functions

We provide a wide range of built-in functions for users to use. The following is a list of built-in functions. Simply write import greptime or from greptime import * at the beginning of your script to use them.

Vector functions

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.
percentileCalculate the q-th percentile of a vector v0. similar to numpy.percentile.
scipy_stats_norm_cdfCalculate the cumulative distribution function for the normal distribution. similar to scipy.stats.norm.cdf.
scipy_stats_norm_pdfCalculate the probability density function for the normal distribution. similar to scipy.stats.norm.pdf.

Math functions

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.

Utility functions & Aggregation functions

These Functions are bound from DataFusion

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.

DataFrame's methods:

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's methods:

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