class_docstr: Merge rows whose timestamp are seconds apart
code: def impute(self, input_df):
      import pyspark.sql.functions as f
  
      ori_column_name = self.timestamp_column_name + "_ori"
      df = input_df.withColumnRenamed(
          self.timestamp_column_name, ori_column_name
      )
      merged_df = (
          df.withColumn(
              "add_seconds",
              (
                  f.round(
                      f.second(ori_column_name) / self.time_interval
                  )
                  * self.time_interval
              )
              - f.second(ori_column_name),
          )
          .withColumn(
              self.timestamp_column_name,
              f.from_unixtime(
                  f.unix_timestamp(ori_column_name)
                  + f.col("add_seconds")
              ),
          )
          .drop("add_seconds")
      )
      if self.mode == "max":
          merged_df = merged_df.groupby(
              self.timestamp_column_name
          ).max()
      elif self.mode == "min":
          merged_df = merged_df.groupby(
              self.timestamp_column_name
          ).min()
      elif self.mode == "mean":
          merged_df = merged_df.groupby(
              self.timestamp_column_name
          ).mean()
      elif self.mode == "sum":
          merged_df = merged_df.groupby(
              self.timestamp_column_name
          ).sum()
      elif self.mode == "":
          merged_df
      else:
          from bigdl.nano.utils.common import invalidInputError
  
          invalidInputError(
              False, "Currently only support max/min/mean/sum mode"
          )
  
      return merged_df
  
file_path: BigDL/python/chronos/src/bigdl/chronos/autots/deprecated/preprocessing/impute/impute.py
imports: from bigdl.chronos.autots.deprecated.preprocessing.impute.abstract import BaseImputation
  from bigdl.chronos.autots.deprecated.preprocessing.impute.LastFill import LastFill
  from bigdl.chronos.utils import deprecated
label_desc: Use image node_id 2 for calling the TimeMergeImputor obj's underlying member method code with example usage: obj.impute(input_df) and returns: merged_df