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Version: Python

Arrays

Arrays are an in-memory ordered data structure common in many programming languages. They are typically used to store multiple elements of the same type in an easily iterable manner. Arrays in the Deephaven engine are implemented by Vector and its subclasses.

The Deephaven Query Language comes with its own built-in array functionality.

Usage​

Columns as arrays​

DQL allows queries to access a column's array representation by using the _ suffix on the column name. Use the bracket syntax [] to access items from a column.

from deephaven import new_table
from deephaven.column import int_col

source = new_table([int_col("Values", [1, 2, 3])])

result = source.update(formulas=["UpdatedValues = Values_[i] + 1"])
danger

The special variables, i and ii, are unreliable within a ticking table. Inconsistent results occur since previously created row indexes do not automatically update.

Built-in array methods like size() can be used within queries.

from deephaven import new_table
from deephaven.column import int_col

source = new_table([int_col("Values", [1, 2, 3])])

result = source.update(formulas=["ValuesSize = Values_.size()"])

Convert a column to an array​

Aggregations such as group_by can be used to convert a column into an array. The following example shows how to store a converted array in a table.

from deephaven import new_table
from deephaven.column import int_col

source = new_table([int_col("Values", [1, 2, 3])])
result = source.group_by()

The same bracket syntax and array methods can be used on the resulting array.

Note that Values becomes a column containing an array, thus Values_[0] is used to access the array.

from deephaven import new_table
from deephaven.column import int_col

source = new_table([int_col("Values", [1, 2, 3])])

result = source.group_by().update(
    formulas=["Length = Values_[0].size()", "FirstElement = Values_[0][0]"]
)

Create a slice or subVector​

DQL allows queries to create subVectors or slices of the columns.

from deephaven import new_table
from deephaven.column import double_col

source = new_table([double_col("X", [1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])])

result = source.update(
    formulas=[
        "A= X_.subVector(i-2,i+1)",
        "rolling_mean = avg(A)",
        "rolling_median =median(A)",
        "rolling_sum = sum(A)",
    ]
)