Udf dev 1.3

[suyx1999]

Update 3 UDFs: Percentile, Quantile and Cluster

Fix issues in Percentile and Quantile UDFs

Percentile

• Fix out-of-bounds index issue
• Add according unit tests

Quantile

• Fix incorrect type conversion
• Add according unit tests

Update Cluster UDF

• This function takes a single input time series, splits it into non-overlapping contiguous subsequences (windows) of fixed length l, and clusters those subsequences to discover local patterns or segment structure.

Input series

• One input series only.
• Types: INT32 / INT64 / FLOAT / DOUBLE.
• Points are read in time order; trailing samples that do not fill a full window are dropped (only ⌊n/l⌋ windows are used, where n is the number of valid points).

Parameters

Name	Meaning	Default	Notes
l	Subsequence (window) length	(required)	Positive integer; each window has l consecutive samples.
k	Number of clusters	(required)	Integer ≥ 2.
method	Clustering algorithm	kmeans	Optional: kmeans, kshape, medoidshape (case-insensitive). Defaults to k-means if omitted.
norm	Z-score normalize each subsequence	true	Boolean; if true, each subsequence is standardized before clustering.
maxiter	Maximum iterations	200	Positive integer.
output	Output mode	label	label: one cluster id per window; centroid: concatenate the k centroid vectors in cluster order.
sample_rate	Greedy sampling rate	0.3	Used only when method = medoidshape; must be in (0, 1].

method details

• kmeans: k-means in Euclidean space (optionally after per-window normalization).
• kshape: Assign by shape-based distance (SBD from normalized cross-correlation, NCC); centroids updated via SVD on the cluster matrix.
• medoidshape: Coarse k-means with min(2k, number of windows) clusters, then greedy selection of k representative subsequences; sample_rate controls how many candidates are sampled each round.

Output series

Controlled by output:

output = label (default)

• One output series, type INT32.
• Number of points = number of full windows, ⌊n/l⌋.
• Timestamp of each point = time of the first sample in that window; value = cluster id 0 … k−1.

output = centroid

• One output series, type DOUBLE.
• Number of points = k × l: for clusters 0 → k−1, emit the l components of each centroid in order (concatenated).
• Timestamps are 0, 1, 2, … (placeholders only, no physical time meaning).

[waynextz]

two little issues

[waynextz]

the version of dev/1.3 should be 1.3.x?

[suyx1999]

Have restored the pom file.

[waynextz]

The bat files are not in sbin/winodws folder in dev/1.3 branch.

[suyx1999]

Have restored the bat file and added cluster registration.