Reading trends from RRD in Lua

Code:
-- This function prepare csv table content from data and passed headers

function generateCSVTable(rows, headers)

  if #rows > 0 then

    if #rows[1] > #headers then

      error("There should be " .. tostring(#rows[1]) .. " header columns!")

    end

  end

  

  -- Prepare .csv file

  for k,v in ipairs(rows) do      

      rows[k] = table.concat(v, ",")

    end



  csv = table.concat(headers, ",") .. "\r\n" .. table.concat(rows, "\r\n")

  return csv

end



-- Allows to add columns based on a current row or a previous one to current row

function addColumnsToRow(row, prevRow, columnGetters)

  for k,getter in ipairs(columnGetters) do

    table.insert(row, getter(row, prevRow))

  end

  return row

end



-- Allows to add columns based on a current row or a previous one to every row

function addColumnsToRows(rows, columnGetters)

  local prev = nil

  for k,row in ipairs(rows) do      

    rows[k] = addColumnsToRow(row, prevRow, columnGetters)

    prev = row

    end

  return rows

end



function copyObject(obj)

  return json.decode(json.encode(obj))

end



-- This function prepare export table and .csv file from defined range

function trend_export(name, dates, mode, timestampType)

  

  require('trends')



  -- detect timeShift

  function detectTimeShift(t0, t1)

  t0_isdst, t1_isdst = os.date('*t', t0).isdst, os.date('*t', t1).isdst



    if (t0_isdst ~= t1_isdst) then

      if (t1_isdst) then

        -- change to summertime

        return 1

      else

        -- change to wintertime

        return 2

      end

    else

      return false

    end

  end

  

  require("json")

  dates = copyObject(dates)



  -- Convert word "now" in "start" to data table

  if type(dates['start']) == "string" then

    if dates['start'] == "now" then dates['start'] = os.date("*t", os.time())

    elseif dates['start'] == "yesterday" then dates['start'] = os.date("*t", os.time()-24*3600)

    elseif dates['start'] == "week_ago" then dates['start'] = os.date("*t", os.time()-7*24*3600)

    elseif dates['start'] == "month_ago" then dates['start'] = os.date("*t", os.time()-30*24*3600)

    elseif dates['start'] == "year_ago" then dates['start'] = os.date("*t", os.time()-365*24*3600)

    end

  end



  -- Convert word "now" in "end" to data table

  if type(dates['end']) == "string" then

    if dates['end'] == "now" then dates['end'] = os.date("*t", os.time())

    elseif dates['end'] == "yesterday" then dates['end'] = os.date("*t", os.time()-24*3600)

    elseif dates['end'] == "week_ago" then dates['end'] = os.date("*t", os.time()-7*24*3600)

    elseif dates['end'] == "month_ago" then dates['end'] = os.date("*t", os.time()-30*24*3600)

    elseif dates['end'] == "year_ago" then dates['end'] = os.date("*t", os.time()-365*24*3600)

    end

  end          



  -- Start and end in unix time

  starttime = os.time(dates['start'])

  endtime = os.time(dates['end'])



  -- Invert "start" and "end" when "end" is smaller than "start"

  if starttime > endtime then

    _ = dates['start']

    dates['start'] = dates['end']

    dates['end'] = _

  end



  -- Read trend resolution from DB

  resolution = db:getlist("SELECT resolution*60 FROM trends WHERE name='" .. name .. "'")[1]



  -- Prepare a table with the data which include the whole data from specified range

  if resolution then

      -- Expand a range with a one more day if there is some data in the last day

    if (os.date("%H", endtime)*3600 + os.date("%M", endtime)*60) >= resolution then

      dates['end'].day = dates['end'].day + 1

      raw_data = trends.fetch(name, dates, resolution)

    else

      raw_data = trends.fetch(name, dates, resolution)

    end



    start = 1

    data = {}

    start_timestamp = os.time(dates['start']) + resolution

    -- Cut the data and prepare a table with the data only from specified range

    offset = 0

    skip = 0

    k = 1

    while k <= #raw_data do

      v = raw_data[k]

      

      if k == 1 then last_timestamp = start_timestamp else last_timestamp = current_timestamp end

      current_timestamp = start_timestamp + (k-1) * resolution + offset

            

      timeShiftStatus = detectTimeShift(last_timestamp, current_timestamp)

      if timeShiftStatus then

        if timeShiftStatus == 1 then -- winter->summer

          skip = 6 -- skip 1 hour empty data

          offset = offset - 3600

        elseif timeShiftStatus == 2 then -- summer->winter

          offset = offset + 3600

        end

      end

      

      -- Add to new table only records from specified range

      if current_timestamp >= starttime and current_timestamp <= endtime then

        if timestampType == 'unixepoch' then data[start] = {current_timestamp, v}

        else data[start] = {os.date('%Y.%m.%d %H:%M:%S', current_timestamp), v} end

        start = start+1

      end



      k = k + 1 + skip

      skip = 0

    end

    

    if mode == 'csv' then

      -- Prepare .csv file

      csv = generateCSVTable(data, { "timestamp", "value" })

      return name, csv, resolution

    elseif mode == 'table' then

      return name, data, resolution

    end

  else

      alert('There is no trend with such a name')

  end

end



-- Merge values from multiple trends in one table

function mergeRows(baseRows, rows)

  for k,row in ipairs(baseRows) do

    if k < 3 then log(k, "base", row) end

    table.insert(baseRows[k], rows[k][2])

    if k < 3 then log(k, "next", rows[k]) end

  end

  return baseRows

end



function getMultipleColumnHeader(names)

  local columns = { "timestamp" }

  for k,name in ipairs(names) do

    table.insert(columns, name)

  end

  return columns

end



-- This function prepare export table and .csv file from defined range

function multiple_trend_export(names, dates, mode, timestampType)

  local baseRows = {}

  

  for k,name in ipairs(names) do

    local trend_name, rows = trend_export(name, dates, 'table', timestampType)

    if #baseRows == 0 then

      baseRows = rows

    else

      baseRows = mergeRows(baseRows, rows)

    end

  end

  

  if mode == 'csv' then

    -- Prepare .csv file

    csv = generateCSVTable(baseRows, getMultipleColumnHeader(names))

    return names, csv, resolution

  elseif mode == 'table' then

    return names, baseRows, resolution

  end

end