/*
 * Copyright (c) 2019 TAOS Data, Inc. <jhtao@taosdata.com>
 *
 * This program is free software: you can use, redistribute, and/or modify
 * it under the terms of the GNU Affero General Public License, version 3
 * or later ("AGPL"), as published by the Free Software Foundation.
 *
 * This program is distributed in the hope that it will be useful, but WITHOUT
 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
 * FITNESS FOR A PARTICULAR PURPOSE.
 *
 * You should have received a copy of the GNU Affero General Public License
 * along with this program. If not, see <http://www.gnu.org/licenses/>.
 */

#include "builtinsimpl.h"
#include "function.h"
#include "tdatablock.h"
#include "tfunctionInt.h"
#include "tglobal.h"

#define SET_VAL(_info, numOfElem, res) \
  do {                                 \
    if ((numOfElem) <= 0) {            \
      break;                           \
    }                                  \
    (_info)->numOfRes = (res);         \
  } while (0)

#define LIST_AVG_N(sumT, T)                                               \
  do {                                                                    \
    T* plist = (T*)pCol->pData;                                           \
    for (int32_t i = start; i < numOfRows + pInput->startRowIndex; ++i) { \
      if (colDataIsNull_f(pCol->nullbitmap, i)) {                         \
        continue;                                                         \
      }                                                                   \
                                                                          \
      numOfElem += 1;                                                     \
      pAvgRes->count -= 1;                                                \
      sumT -= plist[i];                                                   \
    }                                                                     \
  } while (0)

typedef struct SAvgRes {
  double  result;
  SSumRes sum;
  int64_t count;
  int16_t type;  // store the original input type, used in merge function
} SAvgRes;

static void floatVectorSumAVX(const float* plist, int32_t numOfRows, SAvgRes* pRes) {
  const int32_t bitWidth = 256;

#if __AVX__
  // find the start position that are aligned to 32bytes address in memory
  int32_t width = (bitWidth>>3u) / sizeof(float);

  int32_t remainder = numOfRows % width;
  int32_t rounds = numOfRows / width;

  const float* p = plist;

  __m256 val;
  __m256 sum = _mm256_setzero_ps();

  for (int32_t i = 0; i < rounds; ++i) {
    val = _mm256_loadu_ps(p);
    sum = _mm256_add_ps(sum, val);
    p += width;
  }

  // let sum up the final results
  const float* q = (const float*)&sum;
  pRes->sum.dsum += q[0] + q[1] + q[2] + q[3] + q[4] + q[5] + q[6] + q[7];

  int32_t startIndex = rounds * width;
  for (int32_t j = 0; j < remainder; ++j) {
    pRes->sum.dsum += plist[j + startIndex];
  }
#endif
}

static void doubleVectorSumAVX(const double* plist, int32_t numOfRows, SAvgRes* pRes) {
  const int32_t bitWidth = 256;

#if __AVX__
  // find the start position that are aligned to 32bytes address in memory
  int32_t width = (bitWidth>>3u) / sizeof(int64_t);

  int32_t remainder = numOfRows % width;
  int32_t rounds = numOfRows / width;

  const double* p = plist;

  __m256d val;
  __m256d sum = _mm256_setzero_pd();

  for (int32_t i = 0; i < rounds; ++i) {
    val = _mm256_loadu_pd(p);
    sum = _mm256_add_pd(sum, val);
    p += width;
  }

  // let sum up the final results
  const double* q = (const double*)&sum;
  pRes->sum.dsum += q[0] + q[1] + q[2] + q[3];

  int32_t startIndex = rounds * width;
  for (int32_t j = 0; j < remainder; ++j) {
    pRes->sum.dsum += plist[j + startIndex];
  }
#endif
}

static void i8VectorSumAVX2(const int8_t* plist, int32_t numOfRows, int32_t type, SAvgRes* pRes) {
  const int32_t bitWidth = 256;

#if __AVX2__
  // find the start position that are aligned to 32bytes address in memory
  int32_t width = (bitWidth>>3u) / sizeof(int64_t);

  int32_t remainder = numOfRows % width;
  int32_t rounds = numOfRows / width;

  __m256i sum = _mm256_setzero_si256();

  if (type == TSDB_DATA_TYPE_TINYINT) {
    const int8_t* p = plist;

    for (int32_t i = 0; i < rounds; ++i) {
      __m128i val = _mm_lddqu_si128((__m128i*)p);
      __m256i extVal = _mm256_cvtepi8_epi64(val);  // only four items will be converted into __m256i
      sum = _mm256_add_epi64(sum, extVal);
      p += width;
    }
  } else {
    const uint8_t* p = (const uint8_t*)plist;

    for(int32_t i = 0; i < rounds; ++i) {
      __m128i val = _mm_lddqu_si128((__m128i*)p);
      __m256i extVal = _mm256_cvtepu8_epi64(val);  // only four items will be converted into __m256i
      sum = _mm256_add_epi64(sum, extVal);
      p += width;
    }
  }

  // let sum up the final results
  const int64_t* q = (const int64_t*)&sum;
  pRes->sum.isum += q[0] + q[1] + q[2] + q[3];

  int32_t startIndex = rounds * width;
  for (int32_t j = 0; j < remainder; ++j) {
    pRes->sum.isum += plist[j + startIndex];
  }
#endif
}

static void i16VectorSumAVX2(const int16_t* plist, int32_t numOfRows, int32_t type, SAvgRes* pRes) {
  const int32_t bitWidth = 256;

#if __AVX2__
  // find the start position that are aligned to 32bytes address in memory
  int32_t width = (bitWidth>>3u) / sizeof(int64_t);

  int32_t remainder = numOfRows % width;
  int32_t rounds = numOfRows / width;

  __m256i sum = _mm256_setzero_si256();

  if (type == TSDB_DATA_TYPE_SMALLINT) {
    const int16_t* p = plist;

    for (int32_t i = 0; i < rounds; ++i) {
      __m128i val = _mm_lddqu_si128((__m128i*)p);
      __m256i extVal = _mm256_cvtepi16_epi64(val);  // only four items will be converted into __m256i
      sum = _mm256_add_epi64(sum, extVal);
      p += width;
    }
  } else {
    const uint8_t* p = (const uint8_t*)plist;

    for(int32_t i = 0; i < rounds; ++i) {
      __m128i val = _mm_lddqu_si128((__m128i*)p);
      __m256i extVal = _mm256_cvtepu16_epi64(val);  // only four items will be converted into __m256i
      sum = _mm256_add_epi64(sum, extVal);
      p += width;
    }
  }

  // let sum up the final results
  const int64_t* q = (const int64_t*)&sum;
  pRes->sum.isum += q[0] + q[1] + q[2] + q[3];

  int32_t startIndex = rounds * width;
  for (int32_t j = 0; j < remainder; ++j) {
    pRes->sum.isum += plist[j + startIndex];
  }
#endif
}

static void i32VectorSumAVX2(const int32_t* plist, int32_t numOfRows, int32_t type, SAvgRes* pRes) {
  const int32_t bitWidth = 256;

#if __AVX2__
  // find the start position that are aligned to 32bytes address in memory
  int32_t width = (bitWidth>>3u) / sizeof(int64_t);

  int32_t remainder = numOfRows % width;
  int32_t rounds = numOfRows / width;

  __m256i sum = _mm256_setzero_si256();

  if (type == TSDB_DATA_TYPE_INT) {
    const int32_t* p = plist;

    for (int32_t i = 0; i < rounds; ++i) {
      __m128i val = _mm_lddqu_si128((__m128i*)p);
      __m256i extVal = _mm256_cvtepi32_epi64(val);  // only four items will be converted into __m256i
      sum = _mm256_add_epi64(sum, extVal);
      p += width;
    }
  } else {
    const uint32_t* p = (const uint32_t*)plist;

    for(int32_t i = 0; i < rounds; ++i) {
      __m128i val = _mm_lddqu_si128((__m128i*)p);
      __m256i extVal = _mm256_cvtepu32_epi64(val);  // only four items will be converted into __m256i
      sum = _mm256_add_epi64(sum, extVal);
      p += width;
    }
  }

  // let sum up the final results
  const int64_t* q = (const int64_t*)&sum;
  pRes->sum.isum += q[0] + q[1] + q[2] + q[3];

  int32_t startIndex = rounds * width;
  for (int32_t j = 0; j < remainder; ++j) {
    pRes->sum.isum += plist[j + startIndex];
  }
#endif
}

static void i64VectorSumAVX2(const int64_t* plist, int32_t numOfRows, SAvgRes* pRes) {
  const int32_t bitWidth = 256;

#if __AVX2__
  // find the start position that are aligned to 32bytes address in memory
  int32_t width = (bitWidth>>3u) / sizeof(int64_t);

  int32_t remainder = numOfRows % width;
  int32_t rounds = numOfRows / width;

  __m256i sum = _mm256_setzero_si256();

  const int64_t* p = plist;

  for (int32_t i = 0; i < rounds; ++i) {
    __m256i val = _mm256_lddqu_si256((__m256i*)p);
    sum = _mm256_add_epi64(sum, val);
    p += width;
  }

  // let sum up the final results
  const int64_t* q = (const int64_t*)&sum;
  pRes->sum.isum += q[0] + q[1] + q[2] + q[3];

  int32_t startIndex = rounds * width;
  for (int32_t j = 0; j < remainder; ++j) {
    pRes->sum.isum += plist[j + startIndex];
  }
#endif
}

int32_t getAvgInfoSize() { return (int32_t)sizeof(SAvgRes); }

bool getAvgFuncEnv(SFunctionNode* UNUSED_PARAM(pFunc), SFuncExecEnv* pEnv) {
  pEnv->calcMemSize = sizeof(SAvgRes);
  return true;
}

bool avgFunctionSetup(SqlFunctionCtx* pCtx, SResultRowEntryInfo* pResultInfo) {
  if (!functionSetup(pCtx, pResultInfo)) {
    return false;
  }

  SAvgRes* pRes = GET_ROWCELL_INTERBUF(pResultInfo);
  memset(pRes, 0, sizeof(SAvgRes));
  return true;
}

static int32_t calculateAvgBySMAInfo(SAvgRes* pRes, int32_t numOfRows, int32_t type, const SColumnDataAgg* pAgg) {
  int32_t numOfElem = numOfRows - pAgg->numOfNull;
  ASSERT(numOfElem >= 0);

  pRes->count += numOfElem;
  if (IS_SIGNED_NUMERIC_TYPE(type)) {
    pRes->sum.isum += pAgg->sum;
  } else if (IS_UNSIGNED_NUMERIC_TYPE(type)) {
    pRes->sum.usum += pAgg->sum;
  } else if (IS_FLOAT_TYPE(type)) {
    pRes->sum.dsum += GET_DOUBLE_VAL((const char*)&(pAgg->sum));
  }

  return numOfElem;
}

static int32_t doAddNumericVector(SColumnInfoData* pCol, int32_t type, SInputColumnInfoData *pInput, SAvgRes* pRes) {
  int32_t start = pInput->startRowIndex;
  int32_t numOfRows = pInput->numOfRows;
  int32_t numOfElems = 0;

  switch (type) {
    case TSDB_DATA_TYPE_TINYINT: {
      int8_t* plist = (int8_t*)pCol->pData;
      for (int32_t i = start; i < numOfRows + start; ++i) {
        if (colDataIsNull_f(pCol->nullbitmap, i)) {
          continue;
        }

        numOfElems += 1;
        pRes->count += 1;
        pRes->sum.isum += plist[i];
      }

      break;
    }

    case TSDB_DATA_TYPE_SMALLINT: {
      int16_t* plist = (int16_t*)pCol->pData;
      for (int32_t i = start; i < numOfRows + start; ++i) {
        if (colDataIsNull_f(pCol->nullbitmap, i)) {
          continue;
        }

        numOfElems += 1;
        pRes->count += 1;
        pRes->sum.isum += plist[i];
      }
      break;
    }

    case TSDB_DATA_TYPE_INT: {
      int32_t* plist = (int32_t*)pCol->pData;
      for (int32_t i = start; i < numOfRows + start; ++i) {
        if (colDataIsNull_f(pCol->nullbitmap, i)) {
          continue;
        }

        numOfElems += 1;
        pRes->count += 1;
        pRes->sum.isum += plist[i];
      }

      break;
    }

    case TSDB_DATA_TYPE_BIGINT: {
      int64_t* plist = (int64_t*)pCol->pData;
      for (int32_t i = start; i < numOfRows + start; ++i) {
        if (colDataIsNull_f(pCol->nullbitmap, i)) {
          continue;
        }

        numOfElems += 1;
        pRes->count += 1;
        pRes->sum.isum += plist[i];
      }
      break;
    }

    case TSDB_DATA_TYPE_UTINYINT: {
      uint8_t* plist = (uint8_t*)pCol->pData;
      for (int32_t i = start; i < numOfRows + start; ++i) {
        if (colDataIsNull_f(pCol->nullbitmap, i)) {
          continue;
        }

        numOfElems += 1;
        pRes->count += 1;
        pRes->sum.usum += plist[i];
      }

      break;
    }

    case TSDB_DATA_TYPE_USMALLINT: {
      uint16_t* plist = (uint16_t*)pCol->pData;
      for (int32_t i = start; i < numOfRows + start; ++i) {
        if (colDataIsNull_f(pCol->nullbitmap, i)) {
          continue;
        }

        numOfElems += 1;
        pRes->count += 1;
        pRes->sum.usum += plist[i];
      }
      break;
    }

    case TSDB_DATA_TYPE_UINT: {
      uint32_t* plist = (uint32_t*)pCol->pData;
      for (int32_t i = start; i < numOfRows + start; ++i) {
        if (colDataIsNull_f(pCol->nullbitmap, i)) {
          continue;
        }

        numOfElems += 1;
        pRes->count += 1;
        pRes->sum.usum += plist[i];
      }

      break;
    }

    case TSDB_DATA_TYPE_UBIGINT: {
      uint64_t* plist = (uint64_t*)pCol->pData;
      for (int32_t i = start; i < numOfRows + start; ++i) {
        if (colDataIsNull_f(pCol->nullbitmap, i)) {
          continue;
        }

        numOfElems += 1;
        pRes->count += 1;
        pRes->sum.usum += plist[i];
      }
      break;
    }

    case TSDB_DATA_TYPE_FLOAT: {
      float* plist = (float*)pCol->pData;
      for (int32_t i = start; i < numOfRows + start; ++i) {
        if (colDataIsNull_f(pCol->nullbitmap, i)) {
          continue;
        }

        numOfElems += 1;
        pRes->count += 1;
        pRes->sum.dsum += plist[i];
      }
      break;
    }

    case TSDB_DATA_TYPE_DOUBLE: {
      double* plist = (double*)pCol->pData;
      for (int32_t i = start; i < numOfRows + start; ++i) {
        if (colDataIsNull_f(pCol->nullbitmap, i)) {
          continue;
        }

        numOfElems += 1;
        pRes->count += 1;
        pRes->sum.dsum += plist[i];
      }
      break;
    }

    default:
      break;
  }

  return numOfElems;
}

int32_t avgFunction(SqlFunctionCtx* pCtx) {
  int32_t       numOfElem = 0;
  const int32_t THRESHOLD_SIZE = 8;

  SInputColumnInfoData* pInput = &pCtx->input;
  SColumnDataAgg*       pAgg = pInput->pColumnDataAgg[0];
  int32_t               type = pInput->pData[0]->info.type;

  SAvgRes* pAvgRes = GET_ROWCELL_INTERBUF(GET_RES_INFO(pCtx));
  pAvgRes->type = type;

  // computing based on the true data block
  SColumnInfoData* pCol = pInput->pData[0];

  int32_t start = pInput->startRowIndex;
  int32_t numOfRows = pInput->numOfRows;

  if (IS_NULL_TYPE(type)) {
    goto _over;
  }

  if (pInput->colDataSMAIsSet) {  // try to use SMA if available
    numOfElem = calculateAvgBySMAInfo(pAvgRes, numOfRows, type, pAgg);
  } else if (!pCol->hasNull) {  // try to employ the simd instructions to speed up the loop
    numOfElem = pInput->numOfRows;
    pAvgRes->count += pInput->numOfRows;

    bool simdAvailable = tsAVXEnable && tsSIMDEnable && (numOfRows > THRESHOLD_SIZE);

    switch(type) {
      case TSDB_DATA_TYPE_UTINYINT:
      case TSDB_DATA_TYPE_TINYINT: {
        const int8_t* plist = (const int8_t*) pCol->pData;

        // 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
        if (simdAvailable) {
          i8VectorSumAVX2(plist, numOfRows, type, pAvgRes);
        } else {
          for (int32_t i = pInput->startRowIndex; i < pInput->numOfRows + pInput->startRowIndex; ++i) {
            pAvgRes->sum.usum += plist[i];
          }
        }
        break;
      }

      case TSDB_DATA_TYPE_USMALLINT:
      case TSDB_DATA_TYPE_SMALLINT: {
        const int16_t* plist = (const int16_t*)pCol->pData;

        // 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
        if (simdAvailable) {
          i16VectorSumAVX2(plist, numOfRows, type, pAvgRes);
        } else {
          for (int32_t i = pInput->startRowIndex; i < pInput->numOfRows + pInput->startRowIndex; ++i) {
            pAvgRes->sum.isum += plist[i];
          }
        }
        break;
      }

      case TSDB_DATA_TYPE_UINT:
      case TSDB_DATA_TYPE_INT: {
        const int32_t* plist = (const int32_t*) pCol->pData;

        // 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
        if (simdAvailable) {
          i32VectorSumAVX2(plist, numOfRows, type, pAvgRes);
        } else {
          for (int32_t i = pInput->startRowIndex; i < pInput->numOfRows + pInput->startRowIndex; ++i) {
            pAvgRes->sum.isum += plist[i];
          }
        }
        break;
      }

      case TSDB_DATA_TYPE_UBIGINT:
      case TSDB_DATA_TYPE_BIGINT: {
        const int64_t* plist = (const int64_t*) pCol->pData;

        // 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
        if (simdAvailable) {
          i64VectorSumAVX2(plist, numOfRows, pAvgRes);
        } else {
          for (int32_t i = pInput->startRowIndex; i < pInput->numOfRows + pInput->startRowIndex; ++i) {
            pAvgRes->sum.isum += plist[i];
          }
        }
        break;
      }

      case TSDB_DATA_TYPE_FLOAT: {
        const float* plist = (const float*) pCol->pData;

        // 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
        if (simdAvailable) {
          floatVectorSumAVX(plist, numOfRows, pAvgRes);
        } else {
          for (int32_t i = pInput->startRowIndex; i < pInput->numOfRows + pInput->startRowIndex; ++i) {
            pAvgRes->sum.dsum += plist[i];
          }
        }
        break;
      }
      case TSDB_DATA_TYPE_DOUBLE: {
        const double* plist = (const double*)pCol->pData;

        // 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
        if (simdAvailable) {
          doubleVectorSumAVX(plist, numOfRows, pAvgRes);
        } else {
          for (int32_t i = pInput->startRowIndex; i < pInput->numOfRows + pInput->startRowIndex; ++i) {
            pAvgRes->sum.dsum += plist[i];
          }
        }
        break;
      }
      default:
        ASSERT(0);
    }
  } else {
    numOfElem = doAddNumericVector(pCol, type, pInput, pAvgRes);
  }

_over:
  // data in the check operation are all null, not output
  SET_VAL(GET_RES_INFO(pCtx), numOfElem, 1);
  return TSDB_CODE_SUCCESS;
}

static void avgTransferInfo(SAvgRes* pInput, SAvgRes* pOutput) {
  pOutput->type = pInput->type;
  if (IS_SIGNED_NUMERIC_TYPE(pOutput->type)) {
    pOutput->sum.isum += pInput->sum.isum;
  } else if (IS_UNSIGNED_NUMERIC_TYPE(pOutput->type)) {
    pOutput->sum.usum += pInput->sum.usum;
  } else {
    pOutput->sum.dsum += pInput->sum.dsum;
  }

  pOutput->count += pInput->count;
}

int32_t avgFunctionMerge(SqlFunctionCtx* pCtx) {
  SInputColumnInfoData* pInput = &pCtx->input;
  SColumnInfoData*      pCol = pInput->pData[0];
  ASSERT(pCol->info.type == TSDB_DATA_TYPE_BINARY);

  SAvgRes* pInfo = GET_ROWCELL_INTERBUF(GET_RES_INFO(pCtx));

  int32_t start = pInput->startRowIndex;

  for (int32_t i = start; i < start + pInput->numOfRows; ++i) {
    char*    data = colDataGetData(pCol, i);
    SAvgRes* pInputInfo = (SAvgRes*)varDataVal(data);
    avgTransferInfo(pInputInfo, pInfo);
  }

  SET_VAL(GET_RES_INFO(pCtx), 1, 1);

  return TSDB_CODE_SUCCESS;
}

int32_t avgInvertFunction(SqlFunctionCtx* pCtx) {
  int32_t numOfElem = 0;

  // Only the pre-computing information loaded and actual data does not loaded
  SInputColumnInfoData* pInput = &pCtx->input;
  SAvgRes* pAvgRes = GET_ROWCELL_INTERBUF(GET_RES_INFO(pCtx));

  // computing based on the true data block
  SColumnInfoData* pCol = pInput->pData[0];

  int32_t start = pInput->startRowIndex;
  int32_t numOfRows = pInput->numOfRows;

  switch (pCol->info.type) {
    case TSDB_DATA_TYPE_TINYINT: {
      LIST_AVG_N(pAvgRes->sum.isum, int8_t);
      break;
    }
    case TSDB_DATA_TYPE_SMALLINT: {
      LIST_AVG_N(pAvgRes->sum.isum, int16_t);
      break;
    }
    case TSDB_DATA_TYPE_INT: {
      LIST_AVG_N(pAvgRes->sum.isum, int32_t);
      break;
    }
    case TSDB_DATA_TYPE_BIGINT: {
      LIST_AVG_N(pAvgRes->sum.isum, int64_t);
      break;
    }
    case TSDB_DATA_TYPE_UTINYINT: {
      LIST_AVG_N(pAvgRes->sum.usum, uint8_t);
      break;
    }
    case TSDB_DATA_TYPE_USMALLINT: {
      LIST_AVG_N(pAvgRes->sum.usum, uint16_t);
      break;
    }
    case TSDB_DATA_TYPE_UINT: {
      LIST_AVG_N(pAvgRes->sum.usum, uint32_t);
      break;
    }
    case TSDB_DATA_TYPE_UBIGINT: {
      LIST_AVG_N(pAvgRes->sum.usum, uint64_t);
      break;
    }
    case TSDB_DATA_TYPE_FLOAT: {
      LIST_AVG_N(pAvgRes->sum.dsum, float);
      break;
    }
    case TSDB_DATA_TYPE_DOUBLE: {
      LIST_AVG_N(pAvgRes->sum.dsum, double);
      break;
    }
    default:
      break;
  }

  // data in the check operation are all null, not output
  SET_VAL(GET_RES_INFO(pCtx), numOfElem, 1);
  return TSDB_CODE_SUCCESS;
}

int32_t avgCombine(SqlFunctionCtx* pDestCtx, SqlFunctionCtx* pSourceCtx) {
  SResultRowEntryInfo* pDResInfo = GET_RES_INFO(pDestCtx);
  SAvgRes*             pDBuf = GET_ROWCELL_INTERBUF(pDResInfo);

  SResultRowEntryInfo* pSResInfo = GET_RES_INFO(pSourceCtx);
  SAvgRes*             pSBuf = GET_ROWCELL_INTERBUF(pSResInfo);
  int16_t              type = pDBuf->type == TSDB_DATA_TYPE_NULL ? pSBuf->type : pDBuf->type;

  if (IS_SIGNED_NUMERIC_TYPE(type)) {
    pDBuf->sum.isum += pSBuf->sum.isum;
  } else if (IS_UNSIGNED_NUMERIC_TYPE(type)) {
    pDBuf->sum.usum += pSBuf->sum.usum;
  } else {
    pDBuf->sum.dsum += pSBuf->sum.dsum;
  }
  pDBuf->count += pSBuf->count;

  return TSDB_CODE_SUCCESS;
}

int32_t avgFinalize(SqlFunctionCtx* pCtx, SSDataBlock* pBlock) {
  SResultRowEntryInfo* pEntryInfo = GET_RES_INFO(pCtx);

  SAvgRes* pRes = GET_ROWCELL_INTERBUF(pEntryInfo);
  int32_t  type = pRes->type;

  if (pRes->count > 0) {
    if (IS_SIGNED_NUMERIC_TYPE(type)) {
      pRes->result = pRes->sum.isum / ((double)pRes->count);
    } else if (IS_UNSIGNED_NUMERIC_TYPE(type)) {
      pRes->result = pRes->sum.usum / ((double)pRes->count);
    } else {
      pRes->result = pRes->sum.dsum / ((double)pRes->count);
    }
  }

  if (pRes->count == 0 || isinf(pRes->result) || isnan(pRes->result)) {
    pEntryInfo->numOfRes = 0;
  } else {
    pEntryInfo->numOfRes = 1;
  }

  return functionFinalize(pCtx, pBlock);
}

int32_t avgPartialFinalize(SqlFunctionCtx* pCtx, SSDataBlock* pBlock) {
  SResultRowEntryInfo* pResInfo = GET_RES_INFO(pCtx);
  SAvgRes*             pInfo = GET_ROWCELL_INTERBUF(GET_RES_INFO(pCtx));
  int32_t              resultBytes = getAvgInfoSize();
  char*                res = taosMemoryCalloc(resultBytes + VARSTR_HEADER_SIZE, sizeof(char));

  memcpy(varDataVal(res), pInfo, resultBytes);
  varDataSetLen(res, resultBytes);

  int32_t          slotId = pCtx->pExpr->base.resSchema.slotId;
  SColumnInfoData* pCol = taosArrayGet(pBlock->pDataBlock, slotId);

  colDataAppend(pCol, pBlock->info.rows, res, false);

  taosMemoryFree(res);
  return pResInfo->numOfRes;
}