Merge pull request #22165 from taosdata/feat/3.0/TD-25271

feature: optimize interval with limit

source/libs/executor/inc/executorInt.h

@@ -25,6 +25,7 @@ extern "C" {
 #include "tsort.h"
 #include "ttszip.h"
 #include "tvariant.h"
+#include "theap.h"
 
 #include "dataSinkMgt.h"
 #include "executil.h"
@@ -417,6 +418,14 @@ typedef struct SIntervalAggOperatorInfo {
   EOPTR_EXEC_MODEL   execModel;          // operator execution model [batch model|stream model]
   STimeWindowAggSupp twAggSup;
   SArray*            pPrevValues;  //  SArray<SGroupKeys> used to keep the previous not null value for interpolation.
+  // for limit optimization
+  bool          limited;
+  int64_t       limit;
+  bool          slimited;
+  int64_t       slimit;
+  uint64_t      curGroupId; // initialize to UINT64_MAX
+  uint64_t      handledGroupNum;
+  BoundedQueue* pBQ;
 } SIntervalAggOperatorInfo;
 
 typedef struct SMergeAlignedIntervalAggOperatorInfo {

source/libs/executor/src/executil.c

@@ -2118,8 +2118,9 @@ int32_t buildGroupIdMapForAllTables(STableListInfo* pTableListInfo, SReadHandle*
     if (code != TSDB_CODE_SUCCESS) {
       return code;
     }
+    if (pScanNode->groupOrderScan) pTableListInfo->numOfOuputGroups = taosArrayGetSize(pTableListInfo->pTableList);
 
-    if (groupSort) {
+    if (groupSort || pScanNode->groupOrderScan) {
       code = sortTableGroup(pTableListInfo);
     }
   }

source/libs/executor/src/operator.c

@@ -275,7 +275,6 @@ SOperatorInfo* createOperator(SPhysiNode* pPhyNode, SExecTaskInfo* pTaskInfo, SR
                               SNode* pTagIndexCond, const char* pUser, const char* dbname) {
   int32_t     type = nodeType(pPhyNode);
   const char* idstr = GET_TASKID(pTaskInfo);
-
   if (pPhyNode->pChildren == NULL || LIST_LENGTH(pPhyNode->pChildren) == 0) {
     SOperatorInfo* pOperator = NULL;
     if (QUERY_NODE_PHYSICAL_PLAN_TABLE_SCAN == type) {

source/libs/executor/src/scanoperator.c

@@ -848,6 +848,7 @@ static SSDataBlock* doTableScan(SOperatorInfo* pOperator) {
       return result;
     }
 
+    while (1) {
       if ((++pInfo->currentGroupId) >= tableListGetOutputGroups(pInfo->base.pTableListInfo)) {
         setOperatorCompleted(pOperator);
         return NULL;
@@ -869,9 +870,7 @@ static SSDataBlock* doTableScan(SOperatorInfo* pOperator) {
       if (result != NULL) {
         return result;
       }
-
-    setOperatorCompleted(pOperator);
-    return NULL;
+    }
   }
 }
 

source/libs/executor/src/timewindowoperator.c

@@ -876,7 +876,67 @@ bool needDeleteWindowBuf(STimeWindow* pWin, STimeWindowAggSupp* pTwSup) {
   return pTwSup->maxTs != INT64_MIN && pWin->ekey < pTwSup->maxTs - pTwSup->deleteMark;
 }
 
-static void hashIntervalAgg(SOperatorInfo* pOperatorInfo, SResultRowInfo* pResultRowInfo, SSDataBlock* pBlock,
+static bool tsKeyCompFn(void* l, void* r, void* param) {
+  TSKEY* lTS = (TSKEY*)l;
+  TSKEY* rTS = (TSKEY*)r;
+  SIntervalAggOperatorInfo* pInfo = param;
+  return pInfo->binfo.outputTsOrder == ORDER_ASC ? *lTS < *rTS : *lTS > *rTS;
+}
+
+static bool isCalculatedWin(SIntervalAggOperatorInfo* pInfo, const STimeWindow* win, uint64_t tableGroupId) {
+  char keyBuf[sizeof(TSKEY) + sizeof(uint64_t)] = {0};
+  SET_RES_WINDOW_KEY(keyBuf, (char*)&win->skey, sizeof(TSKEY), tableGroupId);
+  return tSimpleHashGet(pInfo->aggSup.pResultRowHashTable, keyBuf, GET_RES_WINDOW_KEY_LEN(sizeof(TSKEY))) != NULL;
+}
+
+/**
+ * @brief check if cur window should be filtered out by limit info
+ * @retval true if should be filtered out
+ * @retval false if not filtering out
+ * @note If no limit info, we skip filtering.
+ *       If input/output ts order mismatch, we skip filtering too.
+ *       eg. input ts order: desc, and output ts order: asc, limit: 10
+ *       IntervalOperator should output the first 10 windows, however, we can't find the first 10 windows until we scan
+ *       every tuple in every block.
+ *       And the boundedQueue keeps refreshing all records with smaller ts key.
+ */
+static bool filterWindowWithLimit(SIntervalAggOperatorInfo* pOperatorInfo, STimeWindow* win, uint64_t groupId) {
+  if (!pOperatorInfo->limited  // if no limit info, no filter will be applied
+      || pOperatorInfo->binfo.inputTsOrder !=
+             pOperatorInfo->binfo.outputTsOrder  // if input/output ts order mismatch, no filter
+  ) {
+    return false;
+  }
+  if (pOperatorInfo->limit == 0) return true;
+
+  if (pOperatorInfo->pBQ == NULL) {
+    pOperatorInfo->pBQ = createBoundedQueue(pOperatorInfo->limit - 1, tsKeyCompFn, taosMemoryFree, pOperatorInfo);
+  }
+
+  bool shouldFilter = false;
+  // if BQ has been full, compare it with top of BQ
+  if (taosBQSize(pOperatorInfo->pBQ) == taosBQMaxSize(pOperatorInfo->pBQ) + 1) {
+    PriorityQueueNode* top = taosBQTop(pOperatorInfo->pBQ);
+    shouldFilter = tsKeyCompFn(top->data, &win->skey, pOperatorInfo);
+  }
+  if (shouldFilter) {
+    return true;
+  } else if (isCalculatedWin(pOperatorInfo, win, groupId)) {
+    return false;
+  }
+
+  // cur win not been filtered out and not been pushed into BQ yet, push it into BQ
+  PriorityQueueNode node = {.data = taosMemoryMalloc(sizeof(TSKEY))};
+  *((TSKEY*)node.data) = win->skey;
+
+  if (NULL == taosBQPush(pOperatorInfo->pBQ, &node)) {
+    taosMemoryFree(node.data);
+    return true;
+  }
+  return false;
+}
+
+static bool hashIntervalAgg(SOperatorInfo* pOperatorInfo, SResultRowInfo* pResultRowInfo, SSDataBlock* pBlock,
                             int32_t scanFlag) {
   SIntervalAggOperatorInfo* pInfo = (SIntervalAggOperatorInfo*)pOperatorInfo->info;
 
@@ -891,8 +951,21 @@ static void hashIntervalAgg(SOperatorInfo* pOperatorInfo, SResultRowInfo* pResul
   TSKEY       ts = getStartTsKey(&pBlock->info.window, tsCols);
   SResultRow* pResult = NULL;
 
+  if (tableGroupId != pInfo->curGroupId) {
+    pInfo->handledGroupNum += 1;
+    if (pInfo->slimited && pInfo->handledGroupNum > pInfo->slimit) {
+      return true;
+    } else {
+      pInfo->curGroupId = tableGroupId;
+      destroyBoundedQueue(pInfo->pBQ);
+      pInfo->pBQ = NULL;
+    }
+  }
+
   STimeWindow win =
       getActiveTimeWindow(pInfo->aggSup.pResultBuf, pResultRowInfo, ts, &pInfo->interval, pInfo->binfo.inputTsOrder);
+  if (filterWindowWithLimit(pInfo, &win, tableGroupId)) return false;
+
   int32_t ret = setTimeWindowOutputBuf(pResultRowInfo, &win, (scanFlag == MAIN_SCAN), &pResult, tableGroupId,
                                        pSup->pCtx, numOfOutput, pSup->rowEntryInfoOffset, &pInfo->aggSup, pTaskInfo);
   if (ret != TSDB_CODE_SUCCESS || pResult == NULL) {
@@ -929,7 +1002,7 @@ static void hashIntervalAgg(SOperatorInfo* pOperatorInfo, SResultRowInfo* pResul
   while (1) {
     int32_t prevEndPos = forwardRows - 1 + startPos;
     startPos = getNextQualifiedWindow(&pInfo->interval, &nextWin, &pBlock->info, tsCols, prevEndPos, pInfo->binfo.inputTsOrder);
-    if (startPos < 0) {
+    if (startPos < 0 || filterWindowWithLimit(pInfo, &nextWin, tableGroupId)) {
       break;
     }
     // null data, failed to allocate more memory buffer
@@ -963,6 +1036,7 @@ static void hashIntervalAgg(SOperatorInfo* pOperatorInfo, SResultRowInfo* pResul
   if (pInfo->timeWindowInterpo) {
     saveDataBlockLastRow(pInfo->pPrevValues, pBlock, pInfo->pInterpCols);
   }
+  return false;
 }
 
 void doCloseWindow(SResultRowInfo* pResultRowInfo, const SIntervalAggOperatorInfo* pInfo, SResultRow* pResult) {
@@ -1043,7 +1117,7 @@ static int32_t doOpenIntervalAgg(SOperatorInfo* pOperator) {
 
     // the pDataBlock are always the same one, no need to call this again
     setInputDataBlock(pSup, pBlock, pInfo->binfo.inputTsOrder, scanFlag, true);
-    hashIntervalAgg(pOperator, &pInfo->binfo.resultRowInfo, pBlock, scanFlag);
+    if (hashIntervalAgg(pOperator, &pInfo->binfo.resultRowInfo, pBlock, scanFlag)) break;
   }
 
   initGroupedResultInfo(&pInfo->groupResInfo, pInfo->aggSup.pResultRowHashTable, pInfo->binfo.outputTsOrder);
@@ -1495,6 +1569,7 @@ void destroyIntervalOperatorInfo(void* param) {
 
   cleanupGroupResInfo(&pInfo->groupResInfo);
   colDataDestroy(&pInfo->twAggSup.timeWindowData);
+  destroyBoundedQueue(pInfo->pBQ);
   taosMemoryFreeClear(param);
 }
 
@@ -1658,6 +1733,17 @@ SOperatorInfo* createIntervalOperatorInfo(SOperatorInfo* downstream, SIntervalPh
   pInfo->interval = interval;
   pInfo->twAggSup = as;
   pInfo->binfo.mergeResultBlock = pPhyNode->window.mergeDataBlock;
+  if (pPhyNode->window.node.pLimit) {
+    SLimitNode* pLimit = (SLimitNode*)pPhyNode->window.node.pLimit;
+    pInfo->limited = true;
+    pInfo->limit = pLimit->limit + pLimit->offset;
+  }
+  if (pPhyNode->window.node.pSlimit) {
+    SLimitNode* pLimit = (SLimitNode*)pPhyNode->window.node.pSlimit;
+    pInfo->slimited = true;
+    pInfo->slimit = pLimit->limit + pLimit->offset;
+    pInfo->curGroupId = UINT64_MAX;
+  }
 
   if (pPhyNode->window.pExprs != NULL) {
     int32_t    numOfScalar = 0;

source/libs/planner/src/planLogicCreater.c

@@ -847,7 +847,6 @@ static int32_t createWindowLogicNodeByInterval(SLogicPlanContext* pCxt, SInterva
           : (pSelect->hasTimeLineFunc ? getRequireDataOrder(true, pSelect) : DATA_ORDER_LEVEL_IN_BLOCK);
   pWindow->node.resultDataOrder =
       pCxt->pPlanCxt->streamQuery ? DATA_ORDER_LEVEL_GLOBAL : getRequireDataOrder(true, pSelect);
-
   pWindow->pTspk = nodesCloneNode(pInterval->pCol);
   if (NULL == pWindow->pTspk) {
     nodesDestroyNode((SNode*)pWindow);

source/libs/planner/src/planOptimizer.c

@@ -1562,11 +1562,33 @@ static bool planOptNodeListHasTbname(SNodeList* pKeys) {
 }
 
 static bool partTagsIsOptimizableNode(SLogicNode* pNode) {
-  return ((QUERY_NODE_LOGIC_PLAN_PARTITION == nodeType(pNode) ||
-           (QUERY_NODE_LOGIC_PLAN_AGG == nodeType(pNode) && NULL != ((SAggLogicNode*)pNode)->pGroupKeys &&
-            NULL != ((SAggLogicNode*)pNode)->pAggFuncs)) &&
-          1 == LIST_LENGTH(pNode->pChildren) &&
-          QUERY_NODE_LOGIC_PLAN_SCAN == nodeType(nodesListGetNode(pNode->pChildren, 0)));
+  bool ret = 1 == LIST_LENGTH(pNode->pChildren) &&
+             QUERY_NODE_LOGIC_PLAN_SCAN == nodeType(nodesListGetNode(pNode->pChildren, 0));
+  if (!ret) return ret;
+  switch (nodeType(pNode)) {
+    case QUERY_NODE_LOGIC_PLAN_PARTITION: {
+      if (pNode->pParent && nodeType(pNode->pParent) == QUERY_NODE_LOGIC_PLAN_WINDOW) {
+        SWindowLogicNode* pWindow = (SWindowLogicNode*)pNode->pParent;
+        if (pWindow->winType == WINDOW_TYPE_INTERVAL) {
+          // if interval has slimit, we push down partition node to scan, and scan will set groupOrderScan to true
+          //   we want to skip groups of blocks after slimit satisfied
+          // if interval only has limit, we do not push down partition node to scan
+          //   we want to get grouped output from partition node and make use of limit
+          // if no slimit and no limit, we push down partition node and groupOrderScan is false, cause we do not need
+          //   group ordered output
+          if (!pWindow->node.pSlimit && pWindow->node.pLimit) ret = false;
+        }
+      }
+    } break;
+    case QUERY_NODE_LOGIC_PLAN_AGG: {
+      SAggLogicNode* pAgg = (SAggLogicNode*)pNode;
+      ret = pAgg->pGroupKeys && pAgg->pAggFuncs;
+    } break;
+    default:
+      ret = false;
+      break;
+  }
+  return ret;
 }
 
 static SNodeList* partTagsGetPartKeys(SLogicNode* pNode) {
@@ -1707,6 +1729,8 @@ static int32_t partTagsOptimize(SOptimizeContext* pCxt, SLogicSubplan* pLogicSub
         scanPathOptSetGroupOrderScan(pScan);
         pParent->hasGroupKeyOptimized = true;
       }
+      if (pNode->pParent->pSlimit)
+        pScan->groupOrderScan = true;
 
       NODES_CLEAR_LIST(pNode->pChildren);
       nodesDestroyNode((SNode*)pNode);
@@ -2660,21 +2684,77 @@ static int32_t tagScanOptimize(SOptimizeContext* pCxt, SLogicSubplan* pLogicSubp
 }
 
 static bool pushDownLimitOptShouldBeOptimized(SLogicNode* pNode) {
-  if (NULL == pNode->pLimit || 1 != LIST_LENGTH(pNode->pChildren)) {
+  if ((NULL == pNode->pLimit && pNode->pSlimit == NULL) || 1 != LIST_LENGTH(pNode->pChildren)) {
     return false;
   }
 
   SLogicNode* pChild = (SLogicNode*)nodesListGetNode(pNode->pChildren, 0);
-  // push down to sort node
-  if (QUERY_NODE_LOGIC_PLAN_SORT == nodeType(pChild)) {
-    // if we have pushed down, we skip it
-    if (pChild->pLimit) return false;
-  } else if (QUERY_NODE_LOGIC_PLAN_SCAN != nodeType(pChild) || QUERY_NODE_LOGIC_PLAN_SORT == nodeType(pNode)) {
-    // push down to table scan node
-    // if pNode is sortNode, we skip push down limit info to table scan node
-    return false;
+  if (pChild->pLimit || pChild->pSlimit) return false;
+  return true;
+}
+
+static void swapLimit(SLogicNode* pParent, SLogicNode* pChild) {
+  pChild->pLimit = pParent->pLimit;
+  pParent->pLimit = NULL;
+}
+
+static void cloneLimit(SLogicNode* pParent, SLogicNode* pChild) {
+  SLimitNode* pLimit = NULL;
+  if (pParent->pLimit) {
+    pChild->pLimit = nodesCloneNode(pParent->pLimit);
+    pLimit = (SLimitNode*)pChild->pLimit;
+    pLimit->limit += pLimit->offset;
+    pLimit->offset = 0;
+  }
+
+  if (pParent->pSlimit) {
+    pChild->pSlimit = nodesCloneNode(pParent->pSlimit);
+    pLimit = (SLimitNode*)pChild->pSlimit;
+    pLimit->limit += pLimit->offset;
+    pLimit->offset = 0;
+  }
+}
+
+static bool pushDownLimitHow(SLogicNode* pNodeWithLimit, SLogicNode* pNodeLimitPushTo);
+static bool pushDownLimitTo(SLogicNode* pNodeWithLimit, SLogicNode* pNodeLimitPushTo) {
+  switch (nodeType(pNodeLimitPushTo)) {
+    case QUERY_NODE_LOGIC_PLAN_WINDOW: {
+      SWindowLogicNode* pWindow = (SWindowLogicNode*)pNodeLimitPushTo;
+      if (pWindow->winType != WINDOW_TYPE_INTERVAL) break;
+      cloneLimit(pNodeWithLimit, pNodeLimitPushTo);
+      return true;
     }
+    case QUERY_NODE_LOGIC_PLAN_FILL:
+    case QUERY_NODE_LOGIC_PLAN_SORT: {
+      cloneLimit(pNodeWithLimit, pNodeLimitPushTo);
+      SNode* pChild = NULL;
+      FOREACH(pChild, pNodeLimitPushTo->pChildren) { pushDownLimitHow(pNodeLimitPushTo, (SLogicNode*)pChild); }
       return true;
+    }
+    case QUERY_NODE_LOGIC_PLAN_SCAN:
+      if (nodeType(pNodeWithLimit) == QUERY_NODE_LOGIC_PLAN_PROJECT && pNodeWithLimit->pLimit) {
+        swapLimit(pNodeWithLimit, pNodeLimitPushTo);
+        return true;
+      }
+    default:
+      break;
+  }
+  return false;
+}
+
+static bool pushDownLimitHow(SLogicNode* pNodeWithLimit, SLogicNode* pNodeLimitPushTo) {
+  switch (nodeType(pNodeWithLimit)) {
+    case QUERY_NODE_LOGIC_PLAN_PROJECT:
+    case QUERY_NODE_LOGIC_PLAN_FILL:
+      return pushDownLimitTo(pNodeWithLimit, pNodeLimitPushTo);
+    case QUERY_NODE_LOGIC_PLAN_SORT: {
+      SSortLogicNode* pSort = (SSortLogicNode*)pNodeWithLimit;
+      if (sortPriKeyOptIsPriKeyOrderBy(pSort->pSortKeys)) return pushDownLimitTo(pNodeWithLimit, pNodeLimitPushTo);
+    }
+    default:
+      break;
+  }
+  return false;
 }
 
 static int32_t pushDownLimitOptimize(SOptimizeContext* pCxt, SLogicSubplan* pLogicSubplan) {
@@ -2685,17 +2765,9 @@ static int32_t pushDownLimitOptimize(SOptimizeContext* pCxt, SLogicSubplan* pLog
 
   SLogicNode* pChild = (SLogicNode*)nodesListGetNode(pNode->pChildren, 0);
   nodesDestroyNode(pChild->pLimit);
-  if (QUERY_NODE_LOGIC_PLAN_SORT == nodeType(pChild)) {
-    pChild->pLimit = nodesCloneNode(pNode->pLimit);
-    SLimitNode* pLimit = (SLimitNode*)pChild->pLimit;
-    pLimit->limit += pLimit->offset;
-    pLimit->offset = 0;
-  } else {
-    pChild->pLimit = pNode->pLimit;
-    pNode->pLimit = NULL;
-  }
+  if (pushDownLimitHow(pNode, pChild)) {
     pCxt->optimized = true;
-
+  }
   return TSDB_CODE_SUCCESS;
 }
 
@@ -2996,6 +3068,7 @@ static const SOptimizeRule optimizeRuleSet[] = {
   {.pName = "sortNonPriKeyOptimize",      .optimizeFunc = sortNonPriKeyOptimize},
   {.pName = "SortPrimaryKey",             .optimizeFunc = sortPrimaryKeyOptimize},
   {.pName = "SmaIndex",                   .optimizeFunc = smaIndexOptimize},
+  {.pName = "PushDownLimit",              .optimizeFunc = pushDownLimitOptimize},
   {.pName = "PartitionTags",              .optimizeFunc = partTagsOptimize},
   {.pName = "MergeProjects",              .optimizeFunc = mergeProjectsOptimize},
   {.pName = "EliminateProject",           .optimizeFunc = eliminateProjOptimize},
@@ -3004,7 +3077,6 @@ static const SOptimizeRule optimizeRuleSet[] = {
   {.pName = "RewriteUnique",              .optimizeFunc = rewriteUniqueOptimize},
   {.pName = "LastRowScan",                .optimizeFunc = lastRowScanOptimize},
   {.pName = "TagScan",                    .optimizeFunc = tagScanOptimize},
-  {.pName = "PushDownLimit",              .optimizeFunc = pushDownLimitOptimize},
   {.pName = "TableCountScan",             .optimizeFunc = tableCountScanOptimize},
 };
 // clang-format on

source/libs/planner/src/planSpliter.c

@@ -498,6 +498,18 @@ static int32_t stbSplRewriteFromMergeNode(SMergeLogicNode* pMerge, SLogicNode* p
       }
       break;
     }
+    case QUERY_NODE_LOGIC_PLAN_WINDOW: {
+      SWindowLogicNode* pWindow = (SWindowLogicNode*)pNode;
+      if (pMerge->node.pLimit) {
+        nodesDestroyNode(pMerge->node.pLimit);
+        pMerge->node.pLimit = NULL;
+      }
+      if (pMerge->node.pSlimit) {
+        nodesDestroyNode(pMerge->node.pSlimit);
+        pMerge->node.pSlimit = NULL;
+      }
+      break;
+    }
     default:
       break;
   }

tests/parallel_test/cases.task

@@ -25,6 +25,7 @@
 ,,y,system-test,./pytest.sh python3 ./test.py -f 2-query/nestedQuery_math.py -Q 4
 ,,y,system-test,./pytest.sh python3 ./test.py -f 2-query/nestedQuery_time.py -Q 4
 ,,y,system-test,./pytest.sh python3 ./test.py -f 2-query/nestedQuery_26.py -Q 4
+,,y,system-test,./pytest.sh python3 ./test.py -f 2-query/interval_limit_opt.py -Q 4
 ,,y,system-test,./pytest.sh python3 ./test.py -f 7-tmq/tmqShow.py
 ,,y,system-test,./pytest.sh python3 ./test.py -f 7-tmq/tmqDropStb.py
 ,,y,system-test,./pytest.sh python3 ./test.py -f 7-tmq/subscribeStb0.py

tests/script/tsim/query/r/explain_tsorder.result

@@ -1603,58 +1603,58 @@ QUERY_PLAN:                                  Time Range: [-9223372036854775808,
 taos> select _wstart, last(ts), avg(c2) from meters interval(10s) order by _wstart desc;
          _wstart         |        last(ts)         |          avg(c2)          |
 ================================================================================
- 2022-05-24 00:01:00.000 | 2022-05-24 00:01:08.000 |             210.000000000 |
- 2022-05-23 00:01:00.000 | 2022-05-23 00:01:08.000 |             116.000000000 |
- 2022-05-22 00:01:00.000 | 2022-05-22 00:01:08.000 |             196.000000000 |
- 2022-05-21 00:01:00.000 | 2022-05-21 00:01:08.000 |              11.000000000 |
- 2022-05-20 00:01:00.000 | 2022-05-20 00:01:08.000 |             120.000000000 |
- 2022-05-19 00:01:00.000 | 2022-05-19 00:01:08.000 |             243.000000000 |
- 2022-05-18 00:01:00.000 | 2022-05-18 00:01:08.000 |              58.000000000 |
- 2022-05-17 00:01:00.000 | 2022-05-17 00:01:08.000 |              59.000000000 |
- 2022-05-16 00:01:00.000 | 2022-05-16 00:01:08.000 |             136.000000000 |
- 2022-05-15 00:01:00.000 | 2022-05-15 00:01:08.000 |             234.000000000 |
+ 2022-05-24 00:01:00.000 | 2022-05-24 00:01:08.000 |       210.000000000000000 |
+ 2022-05-23 00:01:00.000 | 2022-05-23 00:01:08.000 |       116.000000000000000 |
+ 2022-05-22 00:01:00.000 | 2022-05-22 00:01:08.000 |       196.000000000000000 |
+ 2022-05-21 00:01:00.000 | 2022-05-21 00:01:08.000 |        11.000000000000000 |
+ 2022-05-20 00:01:00.000 | 2022-05-20 00:01:08.000 |       120.000000000000000 |
+ 2022-05-19 00:01:00.000 | 2022-05-19 00:01:08.000 |       243.000000000000000 |
+ 2022-05-18 00:01:00.000 | 2022-05-18 00:01:08.000 |        58.000000000000000 |
+ 2022-05-17 00:01:00.000 | 2022-05-17 00:01:08.000 |        59.000000000000000 |
+ 2022-05-16 00:01:00.000 | 2022-05-16 00:01:08.000 |       136.000000000000000 |
+ 2022-05-15 00:01:00.000 | 2022-05-15 00:01:08.000 |       234.000000000000000 |
 
 taos> select _wstart, last(ts), avg(c2) from meters interval(10s) order by _wstart asc;
          _wstart         |        last(ts)         |          avg(c2)          |
 ================================================================================
- 2022-05-15 00:01:00.000 | 2022-05-15 00:01:08.000 |             234.000000000 |
- 2022-05-16 00:01:00.000 | 2022-05-16 00:01:08.000 |             136.000000000 |
- 2022-05-17 00:01:00.000 | 2022-05-17 00:01:08.000 |              59.000000000 |
- 2022-05-18 00:01:00.000 | 2022-05-18 00:01:08.000 |              58.000000000 |
- 2022-05-19 00:01:00.000 | 2022-05-19 00:01:08.000 |             243.000000000 |
- 2022-05-20 00:01:00.000 | 2022-05-20 00:01:08.000 |             120.000000000 |
- 2022-05-21 00:01:00.000 | 2022-05-21 00:01:08.000 |              11.000000000 |
- 2022-05-22 00:01:00.000 | 2022-05-22 00:01:08.000 |             196.000000000 |
- 2022-05-23 00:01:00.000 | 2022-05-23 00:01:08.000 |             116.000000000 |
- 2022-05-24 00:01:00.000 | 2022-05-24 00:01:08.000 |             210.000000000 |
+ 2022-05-15 00:01:00.000 | 2022-05-15 00:01:08.000 |       234.000000000000000 |
+ 2022-05-16 00:01:00.000 | 2022-05-16 00:01:08.000 |       136.000000000000000 |
+ 2022-05-17 00:01:00.000 | 2022-05-17 00:01:08.000 |        59.000000000000000 |
+ 2022-05-18 00:01:00.000 | 2022-05-18 00:01:08.000 |        58.000000000000000 |
+ 2022-05-19 00:01:00.000 | 2022-05-19 00:01:08.000 |       243.000000000000000 |
+ 2022-05-20 00:01:00.000 | 2022-05-20 00:01:08.000 |       120.000000000000000 |
+ 2022-05-21 00:01:00.000 | 2022-05-21 00:01:08.000 |        11.000000000000000 |
+ 2022-05-22 00:01:00.000 | 2022-05-22 00:01:08.000 |       196.000000000000000 |
+ 2022-05-23 00:01:00.000 | 2022-05-23 00:01:08.000 |       116.000000000000000 |
+ 2022-05-24 00:01:00.000 | 2022-05-24 00:01:08.000 |       210.000000000000000 |
 
 taos> select _wstart, first(ts), avg(c2) from meters interval(10s) order by _wstart asc;
          _wstart         |        first(ts)        |          avg(c2)          |
 ================================================================================
- 2022-05-15 00:01:00.000 | 2022-05-15 00:01:08.000 |             234.000000000 |
- 2022-05-16 00:01:00.000 | 2022-05-16 00:01:08.000 |             136.000000000 |
- 2022-05-17 00:01:00.000 | 2022-05-17 00:01:08.000 |              59.000000000 |
- 2022-05-18 00:01:00.000 | 2022-05-18 00:01:08.000 |              58.000000000 |
- 2022-05-19 00:01:00.000 | 2022-05-19 00:01:08.000 |             243.000000000 |
- 2022-05-20 00:01:00.000 | 2022-05-20 00:01:08.000 |             120.000000000 |
- 2022-05-21 00:01:00.000 | 2022-05-21 00:01:08.000 |              11.000000000 |
- 2022-05-22 00:01:00.000 | 2022-05-22 00:01:08.000 |             196.000000000 |
- 2022-05-23 00:01:00.000 | 2022-05-23 00:01:08.000 |             116.000000000 |
- 2022-05-24 00:01:00.000 | 2022-05-24 00:01:08.000 |             210.000000000 |
+ 2022-05-15 00:01:00.000 | 2022-05-15 00:01:08.000 |       234.000000000000000 |
+ 2022-05-16 00:01:00.000 | 2022-05-16 00:01:08.000 |       136.000000000000000 |
+ 2022-05-17 00:01:00.000 | 2022-05-17 00:01:08.000 |        59.000000000000000 |
+ 2022-05-18 00:01:00.000 | 2022-05-18 00:01:08.000 |        58.000000000000000 |
+ 2022-05-19 00:01:00.000 | 2022-05-19 00:01:08.000 |       243.000000000000000 |
+ 2022-05-20 00:01:00.000 | 2022-05-20 00:01:08.000 |       120.000000000000000 |
+ 2022-05-21 00:01:00.000 | 2022-05-21 00:01:08.000 |        11.000000000000000 |
+ 2022-05-22 00:01:00.000 | 2022-05-22 00:01:08.000 |       196.000000000000000 |
+ 2022-05-23 00:01:00.000 | 2022-05-23 00:01:08.000 |       116.000000000000000 |
+ 2022-05-24 00:01:00.000 | 2022-05-24 00:01:08.000 |       210.000000000000000 |
 
 taos> select _wstart, first(ts), avg(c2) from meters interval(10s) order by _wstart desc;
          _wstart         |        first(ts)        |          avg(c2)          |
 ================================================================================
- 2022-05-24 00:01:00.000 | 2022-05-24 00:01:08.000 |             210.000000000 |
- 2022-05-23 00:01:00.000 | 2022-05-23 00:01:08.000 |             116.000000000 |
- 2022-05-22 00:01:00.000 | 2022-05-22 00:01:08.000 |             196.000000000 |
- 2022-05-21 00:01:00.000 | 2022-05-21 00:01:08.000 |              11.000000000 |
- 2022-05-20 00:01:00.000 | 2022-05-20 00:01:08.000 |             120.000000000 |
- 2022-05-19 00:01:00.000 | 2022-05-19 00:01:08.000 |             243.000000000 |
- 2022-05-18 00:01:00.000 | 2022-05-18 00:01:08.000 |              58.000000000 |
- 2022-05-17 00:01:00.000 | 2022-05-17 00:01:08.000 |              59.000000000 |
- 2022-05-16 00:01:00.000 | 2022-05-16 00:01:08.000 |             136.000000000 |
- 2022-05-15 00:01:00.000 | 2022-05-15 00:01:08.000 |             234.000000000 |
+ 2022-05-24 00:01:00.000 | 2022-05-24 00:01:08.000 |       210.000000000000000 |
+ 2022-05-23 00:01:00.000 | 2022-05-23 00:01:08.000 |       116.000000000000000 |
+ 2022-05-22 00:01:00.000 | 2022-05-22 00:01:08.000 |       196.000000000000000 |
+ 2022-05-21 00:01:00.000 | 2022-05-21 00:01:08.000 |        11.000000000000000 |
+ 2022-05-20 00:01:00.000 | 2022-05-20 00:01:08.000 |       120.000000000000000 |
+ 2022-05-19 00:01:00.000 | 2022-05-19 00:01:08.000 |       243.000000000000000 |
+ 2022-05-18 00:01:00.000 | 2022-05-18 00:01:08.000 |        58.000000000000000 |
+ 2022-05-17 00:01:00.000 | 2022-05-17 00:01:08.000 |        59.000000000000000 |
+ 2022-05-16 00:01:00.000 | 2022-05-16 00:01:08.000 |       136.000000000000000 |
+ 2022-05-15 00:01:00.000 | 2022-05-15 00:01:08.000 |       234.000000000000000 |
 
 taos> select last(a) as d from (select _wstart as a, last(ts) as b, avg(c2) as c from meters interval(10s)) order by d;
             d            |
@@ -1792,35 +1792,35 @@ taos> select last(b) as d from (select last(ts) as b, avg(c2) as c from meters i
 taos> select _wstart, first(a) as d, avg(c) from (select _wstart as a, last(ts) as b, avg(c2) as c from meters interval(10s) order by a desc) where a > '2022-05-15 00:01:00.000' and a < '2022-05-21 00:01:08.000' interval(5h) fill(linear) order by d desc;
          _wstart         |            d            |          avg(c)           |
 ================================================================================
- 2022-05-20 20:00:00.000 | 2022-05-21 00:01:00.000 |              11.000000000 |
- 2022-05-20 15:00:00.000 | 2022-05-20 18:01:00.000 |              38.250000000 |
- 2022-05-20 10:00:00.000 | 2022-05-20 12:01:00.000 |              65.500000000 |
- 2022-05-20 05:00:00.000 | 2022-05-20 06:01:00.000 |              92.750000000 |
- 2022-05-20 00:00:00.000 | 2022-05-20 00:01:00.000 |             120.000000000 |
- 2022-05-19 19:00:00.000 | 2022-05-19 19:13:00.000 |             144.600000000 |
- 2022-05-19 14:00:00.000 | 2022-05-19 14:25:00.000 |             169.200000000 |
- 2022-05-19 09:00:00.000 | 2022-05-19 09:37:00.000 |             193.800000000 |
- 2022-05-19 04:00:00.000 | 2022-05-19 04:49:00.000 |             218.400000000 |
- 2022-05-18 23:00:00.000 | 2022-05-19 00:01:00.000 |             243.000000000 |
- 2022-05-18 18:00:00.000 | 2022-05-18 19:13:00.000 |             206.000000000 |
- 2022-05-18 13:00:00.000 | 2022-05-18 14:25:00.000 |             169.000000000 |
- 2022-05-18 08:00:00.000 | 2022-05-18 09:37:00.000 |             132.000000000 |
- 2022-05-18 03:00:00.000 | 2022-05-18 04:49:00.000 |              95.000000000 |
- 2022-05-17 22:00:00.000 | 2022-05-18 00:01:00.000 |              58.000000000 |
- 2022-05-17 17:00:00.000 | 2022-05-17 19:13:00.000 |              58.200000000 |
- 2022-05-17 12:00:00.000 | 2022-05-17 14:25:00.000 |              58.400000000 |
- 2022-05-17 07:00:00.000 | 2022-05-17 09:37:00.000 |              58.600000000 |
- 2022-05-17 02:00:00.000 | 2022-05-17 04:49:00.000 |              58.800000000 |
- 2022-05-16 21:00:00.000 | 2022-05-17 00:01:00.000 |              59.000000000 |
- 2022-05-16 16:00:00.000 | 2022-05-16 19:13:00.000 |              74.400000000 |
- 2022-05-16 11:00:00.000 | 2022-05-16 14:25:00.000 |              89.800000000 |
- 2022-05-16 06:00:00.000 | 2022-05-16 09:37:00.000 |             105.200000000 |
- 2022-05-16 01:00:00.000 | 2022-05-16 04:49:00.000 |             120.600000000 |
- 2022-05-15 20:00:00.000 | 2022-05-16 00:01:00.000 |             136.000000000 |
- 2022-05-15 15:00:00.000 | 2022-05-15 18:01:00.000 |             160.500000000 |
- 2022-05-15 10:00:00.000 | 2022-05-15 12:01:00.000 |             185.000000000 |
- 2022-05-15 05:00:00.000 | 2022-05-15 06:01:00.000 |             209.500000000 |
- 2022-05-15 00:00:00.000 | 2022-05-15 00:01:00.000 |             234.000000000 |
+ 2022-05-20 20:00:00.000 | 2022-05-21 00:01:00.000 |        11.000000000000000 |
+ 2022-05-20 15:00:00.000 | 2022-05-20 18:01:00.000 |        38.250000000000000 |
+ 2022-05-20 10:00:00.000 | 2022-05-20 12:01:00.000 |        65.500000000000000 |
+ 2022-05-20 05:00:00.000 | 2022-05-20 06:01:00.000 |        92.750000000000000 |
+ 2022-05-20 00:00:00.000 | 2022-05-20 00:01:00.000 |       120.000000000000000 |
+ 2022-05-19 19:00:00.000 | 2022-05-19 19:13:00.000 |       144.599999999999994 |
+ 2022-05-19 14:00:00.000 | 2022-05-19 14:25:00.000 |       169.199999999999989 |
+ 2022-05-19 09:00:00.000 | 2022-05-19 09:37:00.000 |       193.800000000000011 |
+ 2022-05-19 04:00:00.000 | 2022-05-19 04:49:00.000 |       218.400000000000006 |
+ 2022-05-18 23:00:00.000 | 2022-05-19 00:01:00.000 |       243.000000000000000 |
+ 2022-05-18 18:00:00.000 | 2022-05-18 19:13:00.000 |       206.000000000000000 |
+ 2022-05-18 13:00:00.000 | 2022-05-18 14:25:00.000 |       169.000000000000000 |
+ 2022-05-18 08:00:00.000 | 2022-05-18 09:37:00.000 |       132.000000000000000 |
+ 2022-05-18 03:00:00.000 | 2022-05-18 04:49:00.000 |        95.000000000000000 |
+ 2022-05-17 22:00:00.000 | 2022-05-18 00:01:00.000 |        58.000000000000000 |
+ 2022-05-17 17:00:00.000 | 2022-05-17 19:13:00.000 |        58.200000000000003 |
+ 2022-05-17 12:00:00.000 | 2022-05-17 14:25:00.000 |        58.399999999999999 |
+ 2022-05-17 07:00:00.000 | 2022-05-17 09:37:00.000 |        58.600000000000001 |
+ 2022-05-17 02:00:00.000 | 2022-05-17 04:49:00.000 |        58.799999999999997 |
+ 2022-05-16 21:00:00.000 | 2022-05-17 00:01:00.000 |        59.000000000000000 |
+ 2022-05-16 16:00:00.000 | 2022-05-16 19:13:00.000 |        74.400000000000006 |
+ 2022-05-16 11:00:00.000 | 2022-05-16 14:25:00.000 |        89.799999999999997 |
+ 2022-05-16 06:00:00.000 | 2022-05-16 09:37:00.000 |       105.200000000000003 |
+ 2022-05-16 01:00:00.000 | 2022-05-16 04:49:00.000 |       120.599999999999994 |
+ 2022-05-15 20:00:00.000 | 2022-05-16 00:01:00.000 |       136.000000000000000 |
+ 2022-05-15 15:00:00.000 | 2022-05-15 18:01:00.000 |       160.500000000000000 |
+ 2022-05-15 10:00:00.000 | 2022-05-15 12:01:00.000 |       185.000000000000000 |
+ 2022-05-15 05:00:00.000 | 2022-05-15 06:01:00.000 |       209.500000000000000 |
+ 2022-05-15 00:00:00.000 | 2022-05-15 00:01:00.000 |       234.000000000000000 |
 
 taos> explain verbose true select _wstart, first(a) as d, avg(c) from (select _wstart as a, last(ts) as b, avg(c2) as c from meters interval(10s) order by a desc) where a > '2022-05-15 00:01:00.000' and a < '2022-05-21 00:01:08.000' interval(5h) fill(linear) order by d desc\G;
 *************************** 1.row ***************************
@@ -2673,51 +2673,51 @@ taos> select ts, c2 from d1 order by ts asc, c2 desc limit 5,5;
 taos> select _wstart, first(a) as d, avg(c) from (select _wstart as a, last(ts) as b, avg(c2) as c from meters interval(10s) order by a desc) where a > '2022-05-15 00:01:00.000' and a < '2022-05-21 00:01:08.000' interval(5h) fill(linear) order by avg(c) desc;
          _wstart         |            d            |          avg(c)           |
 ================================================================================
- 2022-05-18 23:00:00.000 | 2022-05-19 00:01:00.000 |             243.000000000 |
- 2022-05-15 00:00:00.000 | 2022-05-15 00:01:00.000 |             234.000000000 |
- 2022-05-19 04:00:00.000 | 2022-05-19 04:49:00.000 |             218.400000000 |
- 2022-05-15 05:00:00.000 | 2022-05-15 06:01:00.000 |             209.500000000 |
- 2022-05-18 18:00:00.000 | 2022-05-18 19:13:00.000 |             206.000000000 |
- 2022-05-19 09:00:00.000 | 2022-05-19 09:37:00.000 |             193.800000000 |
- 2022-05-15 10:00:00.000 | 2022-05-15 12:01:00.000 |             185.000000000 |
- 2022-05-19 14:00:00.000 | 2022-05-19 14:25:00.000 |             169.200000000 |
- 2022-05-18 13:00:00.000 | 2022-05-18 14:25:00.000 |             169.000000000 |
- 2022-05-15 15:00:00.000 | 2022-05-15 18:01:00.000 |             160.500000000 |
- 2022-05-19 19:00:00.000 | 2022-05-19 19:13:00.000 |             144.600000000 |
- 2022-05-15 20:00:00.000 | 2022-05-16 00:01:00.000 |             136.000000000 |
- 2022-05-18 08:00:00.000 | 2022-05-18 09:37:00.000 |             132.000000000 |
- 2022-05-16 01:00:00.000 | 2022-05-16 04:49:00.000 |             120.600000000 |
- 2022-05-20 00:00:00.000 | 2022-05-20 00:01:00.000 |             120.000000000 |
- 2022-05-16 06:00:00.000 | 2022-05-16 09:37:00.000 |             105.200000000 |
- 2022-05-18 03:00:00.000 | 2022-05-18 04:49:00.000 |              95.000000000 |
- 2022-05-20 05:00:00.000 | 2022-05-20 06:01:00.000 |              92.750000000 |
- 2022-05-16 11:00:00.000 | 2022-05-16 14:25:00.000 |              89.800000000 |
- 2022-05-16 16:00:00.000 | 2022-05-16 19:13:00.000 |              74.400000000 |
- 2022-05-20 10:00:00.000 | 2022-05-20 12:01:00.000 |              65.500000000 |
- 2022-05-16 21:00:00.000 | 2022-05-17 00:01:00.000 |              59.000000000 |
- 2022-05-17 02:00:00.000 | 2022-05-17 04:49:00.000 |              58.800000000 |
- 2022-05-17 07:00:00.000 | 2022-05-17 09:37:00.000 |              58.600000000 |
- 2022-05-17 12:00:00.000 | 2022-05-17 14:25:00.000 |              58.400000000 |
- 2022-05-17 17:00:00.000 | 2022-05-17 19:13:00.000 |              58.200000000 |
- 2022-05-17 22:00:00.000 | 2022-05-18 00:01:00.000 |              58.000000000 |
- 2022-05-20 15:00:00.000 | 2022-05-20 18:01:00.000 |              38.250000000 |
- 2022-05-20 20:00:00.000 | 2022-05-21 00:01:00.000 |              11.000000000 |
+ 2022-05-18 23:00:00.000 | 2022-05-19 00:01:00.000 |       243.000000000000000 |
+ 2022-05-15 00:00:00.000 | 2022-05-15 00:01:00.000 |       234.000000000000000 |
+ 2022-05-19 04:00:00.000 | 2022-05-19 04:49:00.000 |       218.400000000000006 |
+ 2022-05-15 05:00:00.000 | 2022-05-15 06:01:00.000 |       209.500000000000000 |
+ 2022-05-18 18:00:00.000 | 2022-05-18 19:13:00.000 |       206.000000000000000 |
+ 2022-05-19 09:00:00.000 | 2022-05-19 09:37:00.000 |       193.800000000000011 |
+ 2022-05-15 10:00:00.000 | 2022-05-15 12:01:00.000 |       185.000000000000000 |
+ 2022-05-19 14:00:00.000 | 2022-05-19 14:25:00.000 |       169.199999999999989 |
+ 2022-05-18 13:00:00.000 | 2022-05-18 14:25:00.000 |       169.000000000000000 |
+ 2022-05-15 15:00:00.000 | 2022-05-15 18:01:00.000 |       160.500000000000000 |
+ 2022-05-19 19:00:00.000 | 2022-05-19 19:13:00.000 |       144.599999999999994 |
+ 2022-05-15 20:00:00.000 | 2022-05-16 00:01:00.000 |       136.000000000000000 |
+ 2022-05-18 08:00:00.000 | 2022-05-18 09:37:00.000 |       132.000000000000000 |
+ 2022-05-16 01:00:00.000 | 2022-05-16 04:49:00.000 |       120.599999999999994 |
+ 2022-05-20 00:00:00.000 | 2022-05-20 00:01:00.000 |       120.000000000000000 |
+ 2022-05-16 06:00:00.000 | 2022-05-16 09:37:00.000 |       105.200000000000003 |
+ 2022-05-18 03:00:00.000 | 2022-05-18 04:49:00.000 |        95.000000000000000 |
+ 2022-05-20 05:00:00.000 | 2022-05-20 06:01:00.000 |        92.750000000000000 |
+ 2022-05-16 11:00:00.000 | 2022-05-16 14:25:00.000 |        89.799999999999997 |
+ 2022-05-16 16:00:00.000 | 2022-05-16 19:13:00.000 |        74.400000000000006 |
+ 2022-05-20 10:00:00.000 | 2022-05-20 12:01:00.000 |        65.500000000000000 |
+ 2022-05-16 21:00:00.000 | 2022-05-17 00:01:00.000 |        59.000000000000000 |
+ 2022-05-17 02:00:00.000 | 2022-05-17 04:49:00.000 |        58.799999999999997 |
+ 2022-05-17 07:00:00.000 | 2022-05-17 09:37:00.000 |        58.600000000000001 |
+ 2022-05-17 12:00:00.000 | 2022-05-17 14:25:00.000 |        58.399999999999999 |
+ 2022-05-17 17:00:00.000 | 2022-05-17 19:13:00.000 |        58.200000000000003 |
+ 2022-05-17 22:00:00.000 | 2022-05-18 00:01:00.000 |        58.000000000000000 |
+ 2022-05-20 15:00:00.000 | 2022-05-20 18:01:00.000 |        38.250000000000000 |
+ 2022-05-20 20:00:00.000 | 2022-05-21 00:01:00.000 |        11.000000000000000 |
 
 taos> select _wstart, first(a) as d, avg(c) from (select _wstart as a, last(ts) as b, avg(c2) as c from meters interval(10s) order by a desc) where a > '2022-05-15 00:01:00.000' and a < '2022-05-21 00:01:08.000' interval(5h) fill(linear) order by avg(c) desc limit 2;
          _wstart         |            d            |          avg(c)           |
 ================================================================================
- 2022-05-18 23:00:00.000 | 2022-05-19 00:01:00.000 |             243.000000000 |
- 2022-05-15 00:00:00.000 | 2022-05-15 00:01:00.000 |             234.000000000 |
+ 2022-05-18 23:00:00.000 | 2022-05-19 00:01:00.000 |       243.000000000000000 |
+ 2022-05-15 00:00:00.000 | 2022-05-15 00:01:00.000 |       234.000000000000000 |
 
 taos> select _wstart, first(a) as d, avg(c) from (select _wstart as a, last(ts) as b, avg(c2) as c from meters interval(10s) order by a desc) where a > '2022-05-15 00:01:00.000' and a < '2022-05-21 00:01:08.000' interval(5h) fill(linear) order by avg(c) desc limit 2,6;
          _wstart         |            d            |          avg(c)           |
 ================================================================================
- 2022-05-19 04:00:00.000 | 2022-05-19 04:49:00.000 |             218.400000000 |
- 2022-05-15 05:00:00.000 | 2022-05-15 06:01:00.000 |             209.500000000 |
- 2022-05-18 18:00:00.000 | 2022-05-18 19:13:00.000 |             206.000000000 |
- 2022-05-19 09:00:00.000 | 2022-05-19 09:37:00.000 |             193.800000000 |
- 2022-05-15 10:00:00.000 | 2022-05-15 12:01:00.000 |             185.000000000 |
- 2022-05-19 14:00:00.000 | 2022-05-19 14:25:00.000 |             169.200000000 |
+ 2022-05-19 04:00:00.000 | 2022-05-19 04:49:00.000 |       218.400000000000006 |
+ 2022-05-15 05:00:00.000 | 2022-05-15 06:01:00.000 |       209.500000000000000 |
+ 2022-05-18 18:00:00.000 | 2022-05-18 19:13:00.000 |       206.000000000000000 |
+ 2022-05-19 09:00:00.000 | 2022-05-19 09:37:00.000 |       193.800000000000011 |
+ 2022-05-15 10:00:00.000 | 2022-05-15 12:01:00.000 |       185.000000000000000 |
+ 2022-05-19 14:00:00.000 | 2022-05-19 14:25:00.000 |       169.199999999999989 |
 
 taos> select last(ts), c2 as d from d1 group by c2 order by c2 desc limit 10;
         last(ts)         |      d      |

tests/system-test/2-query/interval_limit_opt.py

+import taos
+import sys
+import time
+import socket
+import os
+import threading
+import math
+
+from util.log import *
+from util.sql import *
+from util.cases import *
+from util.dnodes import *
+from util.common import *
+# from tmqCommon import *
+
+class TDTestCase:
+    def __init__(self):
+        self.vgroups    = 4
+        self.ctbNum     = 10
+        self.rowsPerTbl = 10000
+        self.duraion = '1h'
+
+    def init(self, conn, logSql, replicaVar=1):
+        self.replicaVar = int(replicaVar)
+        tdLog.debug(f"start to excute {__file__}")
+        tdSql.init(conn.cursor(), False)
+
+    def create_database(self,tsql, dbName,dropFlag=1,vgroups=2,replica=1, duration:str='1d'):
+        if dropFlag == 1:
+            tsql.execute("drop database if exists %s"%(dbName))
+
+        tsql.execute("create database if not exists %s vgroups %d replica %d duration %s"%(dbName, vgroups, replica, duration))
+        tdLog.debug("complete to create database %s"%(dbName))
+        return
+
+    def create_stable(self,tsql, paraDict):
+        colString = tdCom.gen_column_type_str(colname_prefix=paraDict["colPrefix"], column_elm_list=paraDict["colSchema"])
+        tagString = tdCom.gen_tag_type_str(tagname_prefix=paraDict["tagPrefix"], tag_elm_list=paraDict["tagSchema"])
+        sqlString = f"create table if not exists %s.%s (%s) tags (%s)"%(paraDict["dbName"], paraDict["stbName"], colString, tagString)
+        tdLog.debug("%s"%(sqlString))
+        tsql.execute(sqlString)
+        return
+
+    def create_ctable(self,tsql=None, dbName='dbx',stbName='stb',ctbPrefix='ctb',ctbNum=1,ctbStartIdx=0):
+        for i in range(ctbNum):
+            sqlString = "create table %s.%s%d using %s.%s tags(%d, 'tb%d', 'tb%d', %d, %d, %d)" % \
+                    (dbName,ctbPrefix,i+ctbStartIdx,dbName,stbName,(i+ctbStartIdx) % 5,i+ctbStartIdx,i+ctbStartIdx,i+ctbStartIdx,i+ctbStartIdx,i+ctbStartIdx)
+            tsql.execute(sqlString)
+
+        tdLog.debug("complete to create %d child tables by %s.%s" %(ctbNum, dbName, stbName))
+        return
+
+    def insert_data(self,tsql,dbName,ctbPrefix,ctbNum,rowsPerTbl,batchNum,startTs,tsStep):
+        tdLog.debug("start to insert data ............")
+        tsql.execute("use %s" %dbName)
+        pre_insert = "insert into "
+        sql = pre_insert
+
+        for i in range(ctbNum):
+            rowsBatched = 0
+            sql += " %s%d values "%(ctbPrefix,i)
+            for j in range(rowsPerTbl):
+                if (i < ctbNum/2):
+                    sql += "(%d, %d, %d, %d,%d,%d,%d,true,'binary%d', 'nchar%d') "%(startTs + j*tsStep, j%10, j%10, j%10, j%10, j%10, j%10, j%10, j%10)
+                else:
+                    sql += "(%d, %d, NULL, %d,NULL,%d,%d,true,'binary%d', 'nchar%d') "%(startTs + j*tsStep, j%10, j%10, j%10, j%10, j%10, j%10)
+                rowsBatched += 1
+                if ((rowsBatched == batchNum) or (j == rowsPerTbl - 1)):
+                    tsql.execute(sql)
+                    rowsBatched = 0
+                    if j < rowsPerTbl - 1:
+                        sql = "insert into %s%d values " %(ctbPrefix,i)
+                    else:
+                        sql = "insert into "
+        if sql != pre_insert:
+            tsql.execute(sql)
+        tdLog.debug("insert data ............ [OK]")
+        return
+
+    def prepareTestEnv(self):
+        tdLog.printNoPrefix("======== prepare test env include database, stable, ctables, and insert data: ")
+        paraDict = {'dbName':     'test',
+                    'dropFlag':   1,
+                    'vgroups':    2,
+                    'stbName':    'meters',
+                    'colPrefix':  'c',
+                    'tagPrefix':  't',
+                    'colSchema':   [{'type': 'INT', 'count':1},{'type': 'BIGINT', 'count':1},{'type': 'FLOAT', 'count':1},{'type': 'DOUBLE', 'count':1},{'type': 'smallint', 'count':1},{'type': 'tinyint', 'count':1},{'type': 'bool', 'count':1},{'type': 'binary', 'len':10, 'count':1},{'type': 'nchar', 'len':10, 'count':1}],
+                    'tagSchema':   [{'type': 'INT', 'count':1},{'type': 'nchar', 'len':20, 'count':1},{'type': 'binary', 'len':20, 'count':1},{'type': 'BIGINT', 'count':1},{'type': 'smallint', 'count':1},{'type': 'DOUBLE', 'count':1}],
+                    'ctbPrefix':  't',
+                    'ctbStartIdx': 0,
+                    'ctbNum':     100,
+                    'rowsPerTbl': 10000,
+                    'batchNum':   3000,
+                    'startTs':    1537146000000,
+                    'tsStep':     600000}
+
+        paraDict['vgroups'] = self.vgroups
+        paraDict['ctbNum'] = self.ctbNum
+        paraDict['rowsPerTbl'] = self.rowsPerTbl
+
+        tdLog.info("create database")
+        self.create_database(tsql=tdSql, dbName=paraDict["dbName"], dropFlag=paraDict["dropFlag"], vgroups=paraDict["vgroups"], replica=self.replicaVar, duration=self.duraion)
+
+        tdLog.info("create stb")
+        self.create_stable(tsql=tdSql, paraDict=paraDict)
+
+        tdLog.info("create child tables")
+        self.create_ctable(tsql=tdSql, dbName=paraDict["dbName"], \
+                stbName=paraDict["stbName"],ctbPrefix=paraDict["ctbPrefix"],\
+                ctbNum=paraDict["ctbNum"],ctbStartIdx=paraDict["ctbStartIdx"])
+        self.insert_data(tsql=tdSql, dbName=paraDict["dbName"],\
+                ctbPrefix=paraDict["ctbPrefix"],ctbNum=paraDict["ctbNum"],\
+                rowsPerTbl=paraDict["rowsPerTbl"],batchNum=paraDict["batchNum"],\
+                startTs=paraDict["startTs"],tsStep=paraDict["tsStep"])
+        return
+
+    def check_first_rows(self, all_rows, limited_rows, offset: int = 0):
+        for i in range(0, len(limited_rows) - 1):
+            if limited_rows[i] != all_rows[i + offset]:
+                tdLog.info("row: %d, row in all:    %s" % (i+offset+1, str(all_rows[i+offset])))
+                tdLog.info("row: %d, row in limted: %s" % (i+1, str(limited_rows[i])))
+                tdLog.exit("row data check failed")
+        tdLog.info("all rows are the same as query without limit..")
+
+    def query_and_check_with_slimit(self, sql: str, max_limit: int, step: int, offset: int = 0):
+        self.query_and_check_with_limit(sql, max_limit, step, offset, ' slimit ')
+
+    def query_and_check_with_limit(self, sql: str, max_limit: int, step: int, offset: int = 0, limit_str: str = ' limit '):
+        for limit in range(0, max_limit, step):
+            limited_sql = sql + limit_str + str(offset) + "," + str(limit)
+            tdLog.info("query with sql: %s "  % (sql) + limit_str + " %d,%d" % (offset, limit))
+            all_rows = tdSql.getResult(sql)
+            limited_rows = tdSql.getResult(limited_sql)
+            tdLog.info("all rows: %d, limited rows: %d" % (len(all_rows), len(limited_rows)))
+            if limit_str == ' limit ':
+                if limit + offset <= len(all_rows) and len(limited_rows) != limit:
+                    tdLog.exit("limited sql has less rows than limit value which is not right, \
+                            limit: %d, limited_rows: %d, all_rows: %d, offset: %d" % (limit, len(limited_rows), len(all_rows), offset))
+                elif limit + offset > len(all_rows) and offset < len(all_rows) and offset + len(limited_rows) != len(all_rows):
+                    tdLog.exit("limited sql has less rows than all_rows which is not right, \
+                            limit: %d, limited_rows: %d, all_rows: %d, offset: %d" % (limit, len(limited_rows), len(all_rows), offset))
+                elif offset >= len(all_rows) and len(limited_rows) != 0:
+                    tdLog.exit("limited rows should be zero, \
+                            limit: %d, limited_rows: %d, all_rows: %d, offset: %d" % (limit, len(limited_rows), len(all_rows), offset))
+
+            self.check_first_rows(all_rows, limited_rows, offset)
+
+    def test_interval_limit_asc(self, offset: int = 0):
+        sqls = ["select _wstart, _wend, count(*), sum(c1), avg(c2), first(ts) from meters interval(1s) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), first(ts) from meters interval(1m) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), first(ts) from meters interval(1h) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), first(ts) from meters interval(1d) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), first(ts) from t1 interval(1s) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), first(ts) from t1 interval(1m) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), first(ts) from t1 interval(1h) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), first(ts) from t1 interval(1d) "]
+        for sql in sqls:
+            self.query_and_check_with_limit(sql, 5000, 500, offset)
+
+    def test_interval_limit_desc(self, offset: int = 0):
+        sqls = ["select _wstart, _wend, count(*), sum(c1), avg(c2), last(ts) from meters interval(1s) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), last(ts) from meters interval(1m) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), last(ts) from meters interval(1h) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), last(ts) from meters interval(1d) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), last(ts) from t1 interval(1s) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), last(ts) from t1 interval(1m) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), last(ts) from t1 interval(1h) ",
+                "select _wstart, _wend, count(*), sum(c1), avg(c2), last(ts) from t1 interval(1d) "]
+        for sql in sqls:
+            self.query_and_check_with_limit(sql, 5000, 500, offset)
+
+    def test_interval_limit_offset(self):
+        for offset in range(0, 1000, 500):
+            self.test_interval_limit_asc(offset)
+            self.test_interval_limit_desc(offset)
+            self.test_interval_fill_limit(offset)
+            self.test_interval_order_by_limit(offset)
+            self.test_interval_partition_by_slimit(offset)
+
+    def test_interval_fill_limit(self, offset: int = 0):
+        sqls = [
+                "select _wstart as a, _wend as b, count(*), sum(c1), avg(c2), first(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-09-17 09:30:00.000' interval(1s) fill(linear)",
+                "select _wstart as a, _wend as b, count(*), sum(c1), avg(c2), first(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-09-17 09:30:00.000' interval(1m) fill(linear)",
+                "select _wstart as a, _wend as b, count(*), sum(c1), avg(c2), first(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-09-17 09:30:00.000' interval(1h) fill(linear)",
+                "select _wstart as a, _wend as b, count(*), sum(c1), avg(c2), first(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-09-17 09:30:00.000' interval(1d) fill(linear)"
+                ]
+        for sql in sqls:
+            self.query_and_check_with_limit(sql, 5000, 1000, offset)
+
+    def test_interval_order_by_limit(self, offset: int = 0):
+        sqls = [
+                "select _wstart as a, _wend as b, count(*), sum(c1), avg(c2), first(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' interval(1m) order by b",
+                "select _wstart as a, _wend as b, count(*), sum(c1), avg(c2), first(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' interval(1m) order by a desc",
+                "select _wstart as a, _wend as b, count(*), sum(c1), avg(c2), last(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' interval(1m) order by a desc",
+                "select _wstart as a, _wend as b, count(*), sum(c1), avg(c2), first(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' interval(1m) order by count(*), sum(c1), a",
+                "select _wstart as a, _wend as b, count(*), sum(c1), avg(c2), first(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' interval(1m) order by a, count(*), sum(c1)",
+                "select _wstart as a, _wend as b, count(*), sum(c1), avg(c2), first(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' interval(1m) fill(linear) order by b",
+                "select _wstart as a, _wend as b, count(*), sum(c1), avg(c2), first(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' interval(1m) fill(linear) order by a desc",
+                "select _wstart as a, _wend as b, count(*), sum(c1), last(c2), first(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' interval(1m) fill(linear) order by a desc",
+                "select _wstart as a, _wend as b, count(*), sum(c1), avg(c2), first(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' interval(1m) fill(linear) order by count(*), sum(c1), a",
+                "select _wstart as a, _wend as b, count(*), sum(c1), avg(c2), first(ts) from meters \
+                        where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' interval(1m) fill(linear) order by a, count(*), sum(c1)",
+                ]
+        for sql in sqls:
+            self.query_and_check_with_limit(sql, 6000, 2000, offset)
+
+    def test_interval_partition_by_slimit(self, offset: int = 0):
+        sqls = [
+                "select _wstart as a, _wend as b, count(*), sum(c1), last(c2), first(ts) from meters "
+                "where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' partition by t1 interval(1m)",
+                "select _wstart as a, _wend as b, count(*), sum(c1), last(c2), first(ts) from meters "
+                "where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' partition by t1 interval(1h)",
+                "select _wstart as a, _wend as b, count(*), sum(c1), last(c2), first(ts) from meters "
+                "where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' partition by c3 interval(1m)",
+                ]
+        for sql in sqls:
+            self.query_and_check_with_slimit(sql, 10, 2, offset)
+
+    def test_interval_partition_by_slimit_limit(self):
+        sql = "select * from (select _wstart as a, _wend as b, count(*), sum(c1), last(c2), first(ts),c3 from meters " \
+                "where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' partition by c3 interval(1m) slimit 10 limit 2) order by c3 asc"
+        tdSql.query(sql)
+        tdSql.checkRows(20)
+        tdSql.checkData(0, 4, 0)
+        tdSql.checkData(1, 4, 0)
+        tdSql.checkData(2, 4, 1)
+        tdSql.checkData(3, 4, 1)
+        tdSql.checkData(18, 4, 9)
+        tdSql.checkData(19, 4, 9)
+
+        sql = "select * from (select _wstart as a, _wend as b, count(*), sum(c1), last(c2), first(ts),c3 from meters " \
+                "where ts >= '2018-09-17 09:00:00.000' and ts <= '2018-10-17 09:30:00.000' partition by c3 interval(1m) slimit 2,2 limit 2) order by c3 asc"
+        tdSql.query(sql)
+        tdSql.checkRows(4)
+        tdSql.checkData(0, 4, 2)
+        tdSql.checkData(1, 4, 2)
+        tdSql.checkData(2, 4, 9)
+        tdSql.checkData(3, 4, 9)
+
+    def run(self):
+        self.prepareTestEnv()
+        self.test_interval_limit_offset()
+        self.test_interval_partition_by_slimit_limit()
+
+    def stop(self):
+        tdSql.close()
+        tdLog.success(f"{__file__} successfully executed")
+
+event = threading.Event()
+
+tdCases.addLinux(__file__, TDTestCase())
+tdCases.addWindows(__file__, TDTestCase())