Add TsFile (converted from ICOS-AI/live_cpu_utilization)

README.md

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+---
+license: mit
+tags:
+- tsfile
+- timeseries
+- time-series
+- format:tsfile
+pretty_name: live_cpu_utilization (TsFile)
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: live_cpu_utilization_g0.tsfile
+  - split: train
+    path: live_cpu_utilization_g1.tsfile
+---
+
+# live_cpu_utilization (TsFile)
+
+Apache TsFile version of [`ICOS-AI/live_cpu_utilization`](https://huggingface.co/datasets/ICOS-AI/live_cpu_utilization).
+
+## Overview
+
+- **Tables:** 2 TsFile table(s), 2,488 rows in total.
+  - `live_cpu_utilization_g0`: 499 rows, 2023-06-28 16:26:24 鈫?2023-06-29 01:05:58 (UTC)
+  - `live_cpu_utilization_g1`: 1,989 rows, 2024-09-02 13:55:00 鈫?2024-09-09 11:35:00 (UTC)
+
+## Schema (TsFile structure)
+
+### `live_cpu_utilization_g0.tsfile`
+
+- **Time** (INT64, milliseconds) 鈥?the source `Date` column.
+- **TAG**: none 鈥?the table is stored as a single device.
+- **FIELD** (10): `CPU_Core_0_Usage` (string), `CPU_Core_1_Usage` (double), `CPU_Core_2_Usage` (double), `CPU_Core_3_Usage` (double), `CPU_Core_4_Usage` (double), `CPU_Core_5_Usage` (double), `CPU_Core_6_Usage` (double), `CPU_Core_7_Usage` (double), `CPU_Usage_All_Cores` (double), `Memory_Usage` (double)
+
+### `live_cpu_utilization_g1.tsfile`
+
+- **Time** (INT64, milliseconds) 鈥?the source `timestamp` column.
+- **TAG**: none 鈥?the table is stored as a single device.
+- **FIELD** (2): `CPU` (double), `MEM` (double)
+
+## Conversion notes
+
+- One TsFile per source table (2 tables). Tables whose source carries several entities per file are stored as one device per entity.
+- Time = the table's own clock column as INT64 milliseconds. The clock columns used here are `Date`, `timestamp`.
+- No column is dropped. Rows that share a timestamp inside one device are ordered by a 1 ms step in stable source order, so calendar columns keep their exact day.
+
+## Usage
+
+> **Read this dataset with the Java SDK.** It is written with the `zstd` compressor. The Apache TsFile Java SDK reads every compressor, but the Python SDK (`pip install tsfile`) implements only `UNCOMPRESSED`, `SNAPPY`, `GZIP` and `LZ4`; opening this file with it yields no rows.
+
+Read a converted file with the Apache TsFile Java SDK (`org.apache.tsfile:tsfile`):
+
+```java
+import org.apache.tsfile.file.metadata.IDeviceID;
+import org.apache.tsfile.read.TsFileReader;
+import org.apache.tsfile.read.TsFileSequenceReader;
+import org.apache.tsfile.read.common.Path;
+import org.apache.tsfile.read.expression.QueryExpression;
+import org.apache.tsfile.read.query.dataset.QueryDataSet;
+import org.apache.tsfile.write.schema.MeasurementSchema;
+
+import java.util.ArrayList;
+import java.util.List;
+
+String path = "live_cpu_utilization_g0.tsfile";
+try (TsFileSequenceReader sequenceReader = new TsFileSequenceReader(path);
+     TsFileReader reader = new TsFileReader(sequenceReader)) {
+    // Devices are enumerated as IDeviceID objects. Tables with TAG columns
+    // have multi-segment device ids that cannot be rebuilt from their string
+    // form, so always use getAllDevices() rather than getAllDeviceIds().
+    for (IDeviceID device : sequenceReader.getAllDevices()) {
+        List<Path> paths = new ArrayList<>();
+        for (MeasurementSchema schema : reader.getMeasurement(device)) {
+            String name = schema.getMeasurementName();
+            if (name != null && !name.isEmpty() && !name.equalsIgnoreCase("Time")) {
+                paths.add(new Path(device, name, true));
+            }
+        }
+        QueryDataSet dataSet = reader.query(QueryExpression.create(paths, null));
+        while (dataSet.hasNext()) {
+            System.out.println(dataSet.next());
+        }
+    }
+}
+```
+
+## Source & license
+
+- Original dataset: [`ICOS-AI/live_cpu_utilization`](https://huggingface.co/datasets/ICOS-AI/live_cpu_utilization)
+- License: mit (as declared by the original dataset).