docs: mockdatasoruce.py

docs/examples/python/highvolume_faster_queue.py

@@ -9,6 +9,7 @@ import time
 import os
 from multiprocessing import Process
 from faster_fifo import Queue
+from mockdatasoruce import MockDataSource
 from queue import Empty
 from typing import List
 
@@ -40,57 +41,17 @@ def get_connection():
     return taos.connect(host=host, port=int(port), user=user, password=password)
 
 
-# ANCHOR: MockDataSource
-class MockDataSource:
-    location = ["LosAngeles", "SanDiego", "Hollywood", "Compton", "San Francisco"]
-    current = [8.8, 10.7, 9.9, 8.9, 9.4]
-    voltage = [119, 116, 111, 113, 118]
-    phase = [0.32, 0.34, 0.33, 0.329, 0.141]
-    max_rows_per_table = 10 ** 9
-
-    def __init__(self, tb_name_prefix, table_count):
-        self.table_name_prefix = tb_name_prefix
-        self.table_count = table_count
-        self.start_ms = round(time.time() * 1000) - self.max_rows_per_table * 100
-
-    def __iter__(self):
-        self.row = 0
-        self.table_id = -1
-        return self
-
-    def __next__(self):
-        """
-        next 100 rows of current table
-        """
-        self.table_id += 1
-        if self.table_id == self.table_count:
-            self.table_id = 0
-        if self.row >= self.max_rows_per_table:
-            raise StopIteration
-        rows = []
-
-        while len(rows) < 100:
-            self.row += 1
-            ts = self.start_ms + 100 * self.row
-            group_id = self.table_id % 5 if self.table_id % 5 == 0 else self.table_id % 5 + 1
-            tb_name = self.table_name_prefix + '_' + str(self.table_id)
-            ri = self.row % 5
-            rows.append(f"{tb_name},{ts},{self.current[ri]},{self.voltage[ri]},{self.phase[ri]},{self.location[ri]},{group_id}")
-        return self.table_id, rows
-
-
-# ANCHOR_END: MockDataSource
-
 # ANCHOR: read
 def run_read_task(task_id: int, task_queues: List[Queue]):
     table_count_per_task = TABLE_COUNT // READ_TASK_COUNT
     data_source = MockDataSource(f"tb{task_id}", table_count_per_task)
     try:
-        for table_id, rows in data_source:
+        for batch in data_source:
+            for table_id, row in batch:
                 # hash data to different queue
                 i = table_id % len(task_queues)
                 # block putting forever when the queue is full
-            task_queues[i].put_many(rows, block=True, timeout=-1)
+                task_queues[i].put(row, block=True, timeout=-1)
     except KeyboardInterrupt:
         pass
 

docs/examples/python/mockdatasoruce.py

+import time
+
+
+class MockDataSource:
+    samples = [
+        "LosAngeles,0,8.8,119,0.32",
+        "SanDiego,1,10.7,116,0.34",
+        "Hollywood,2,9.9,111,0.33",
+        "Compton,3,8.9,113,0.329",
+        "San Francisco,4,9.4,118,0.141"
+    ]
+
+    def __init__(self, tb_name_prefix, table_count):
+        self.table_name_prefix = tb_name_prefix + "_"
+        self.table_count = table_count
+        self.max_rows = 10000000
+        self.start_ms = round(time.time() * 1000) - self.max_rows * 100
+        self.data = self._init_data()
+
+    def _init_data(self):
+        lines = self.samples * (self.table_count // 5 + 1)
+        data = []
+        for i in range(self.table_count):
+            table_name = self.table_name_prefix + str(i)
+            # tbName,location,groupId,current,voltage,phase
+            row = table_name + ',' + lines[i]
+            data.append((i, row))  # tableId, row
+        return data
+
+    def __iter__(self):
+        self.row = 0
+        return self
+
+    def __next__(self):
+        """
+        next row for each table.
+        [(tableId, row),(tableId, row)]
+        """
+        self.row += 1
+        ts = self.start_ms + 100 * self.row
+        # just add timestamp to each row
+        return map(lambda t: (t[0], str(ts) + "," + t[1]), self.data)
+
+
+if __name__ == '__main__':
+    """
+    Test performance of MockDataSource
+    """
+    from threading import Thread
+
+    count = 0
+
+
+    def consume():
+        global count
+        for data in MockDataSource("1", 1000):
+            count += len(data)
+
+
+    Thread(target=consume).start()
+    while True:
+        time.sleep(1)
+        print(count)