def test_shiftleft(self):
self.spark.range(10).select(
assert_true(
shiftLeft(col("id"), 2) == shiftleft(col("id"), 2))).collect()
def tocolumns(df, expr):
import pyspark.sql.functions as fcns
if isinstance(expr, histbook.expr.Const):
return fcns.lit(expr.value)
elif isinstance(expr, (histbook.expr.Name, histbook.expr.Predicate)):
return df[expr.value]
elif isinstance(expr, histbook.expr.Call):
if expr.fcn == "abs" or expr.fcn == "fabs":
return fcns.abs(tocolumns(df, expr.args[0]))
elif expr.fcn == "max" or expr.fcn == "fmax":
return fcns.greatest(*[tocolumns(df, x) for x in expr.args])
elif expr.fcn == "min" or expr.fcn == "fmin":
return fcns.least(*[tocolumns(df, x) for x in expr.args])
elif expr.fcn == "arccos":
return fcns.acos(tocolumns(df, expr.args[0]))
elif expr.fcn == "arccosh":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "arcsin":
return fcns.asin(tocolumns(df, expr.args[0]))
elif expr.fcn == "arcsinh":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "arctan2":
return fcns.atan2(tocolumns(df, expr.args[0]),
tocolumns(df, expr.args[1]))
elif expr.fcn == "arctan":
return fcns.atan(tocolumns(df, expr.args[0]))
elif expr.fcn == "arctanh":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "ceil":
return fcns.ceil(tocolumns(df, expr.args[0]))
elif expr.fcn == "copysign":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "cos":
return fcns.cos(tocolumns(df, expr.args[0]))
elif expr.fcn == "cosh":
return fcns.cosh(tocolumns(df, expr.args[0]))
elif expr.fcn == "rad2deg":
return tocolumns(df, expr.args[0]) * (180.0 / math.pi)
elif expr.fcn == "erfc":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "erf":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "exp":
return fcns.exp(tocolumns(df, expr.args[0]))
elif expr.fcn == "expm1":
return fcns.expm1(tocolumns(df, expr.args[0]))
elif expr.fcn == "factorial":
return fcns.factorial(tocolumns(df, expr.args[0]))
elif expr.fcn == "floor":
return fcns.floor(tocolumns(df, expr.args[0]))
elif expr.fcn == "fmod":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "gamma":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "hypot":
return fcns.hypot(tocolumns(df, expr.args[0]),
tocolumns(df, expr.args[1]))
elif expr.fcn == "isinf":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "isnan":
return fcns.isnan(tocolumns(df, expr.args[0]))
elif expr.fcn == "lgamma":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "log10":
return fcns.log10(tocolumns(df, expr.args[0]))
elif expr.fcn == "log1p":
return fcns.log1p(tocolumns(df, expr.args[0]))
elif expr.fcn == "log":
return fcns.log(tocolumns(df, expr.args[0]))
elif expr.fcn == "pow":
return fcns.pow(tocolumns(df, expr.args[0]),
tocolumns(df, expr.args[1]))
elif expr.fcn == "deg2rad":
return tocolumns(df, expr.args[0]) * (math.pi / 180.0)
elif expr.fcn == "sinh":
return fcns.sinh(tocolumns(df, expr.args[0]))
elif expr.fcn == "sin":
return fcns.sin(tocolumns(df, expr.args[0]))
elif expr.fcn == "sqrt":
return fcns.sqrt(tocolumns(df, expr.args[0]))
elif expr.fcn == "tanh":
return fcns.tanh(tocolumns(df, expr.args[0]))
elif expr.fcn == "tan":
return fcns.tan(tocolumns(df, expr.args[0]))
elif expr.fcn == "trunc":
raise NotImplementedError(
expr.fcn) # FIXME (fcns.trunc is for dates)
elif expr.fcn == "xor":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "conjugate":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "exp2":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "heaviside":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "isfinite":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "left_shift" and isinstance(expr.args[1],
histbook.expr.Const):
return fcns.shiftLeft(tocolumns(df, expr.args[0]),
expr.args[1].value)
elif expr.fcn == "log2":
return fcns.log2(tocolumns(df, expr.args[0]))
elif expr.fcn == "logaddexp2":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "logaddexp":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "mod" or expr.fcn == "fmod":
return tocolumns(df, expr.args[0]) % tocolumns(df, expr.args[1])
elif expr.fcn == "right_shift" and isinstance(expr.args[1],
histbook.expr.Const):
return fcns.shiftRight(tocolumns(df, expr.args[0]),
expr.args[1].value)
elif expr.fcn == "rint":
return fcns.rint(tocolumns(df, expr.args[0]))
elif expr.fcn == "sign":
raise NotImplementedError(expr.fcn) # FIXME
elif expr.fcn == "where":
return fcns.when(tocolumns(df, expr.args[0]),
tocolumns(df, expr.args[1])).otherwise(
tocolumns(df, expr.args[2]))
elif expr.fcn == "numpy.equal":
return tocolumns(df, expr.args[0]) == tocolumns(df, expr.args[1])
elif expr.fcn == "numpy.not_equal":
return tocolumns(df, expr.args[0]) != tocolumns(df, expr.args[1])
elif expr.fcn == "numpy.less":
return tocolumns(df, expr.args[0]) < tocolumns(df, expr.args[1])
elif expr.fcn == "numpy.less_equal":
return tocolumns(df, expr.args[0]) <= tocolumns(df, expr.args[1])
elif expr.fcn == "numpy.isin":
return tocolumns(df, expr.args[0]) in tocolumns(df, expr.args[1])
elif expr.fcn == "numpy.logical_not":
return ~tocolumns(df, expr.args[0])
elif expr.fcn == "numpy.add":
return tocolumns(df, expr.args[0]) + tocolumns(df, expr.args[1])
elif expr.fcn == "numpy.subtract":
return tocolumns(df, expr.args[0]) - tocolumns(df, expr.args[1])
elif expr.fcn == "numpy.multiply":
return tocolumns(df, expr.args[0]) * tocolumns(df, expr.args[1])
elif expr.fcn == "numpy.true_divide":
return tocolumns(df, expr.args[0]) / tocolumns(df, expr.args[1])
elif expr.fcn == "numpy.logical_or":
return tocolumns(df, expr.args[0]) | tocolumns(df, expr.args[1])
elif expr.fcn == "numpy.logical_and":
return tocolumns(df, expr.args[0]) & tocolumns(df, expr.args[1])
else:
raise NotImplementedError(expr.fcn)
else:
raise AssertionError(expr)
