#
# Copyright 2015 LinkedIn Corp. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#

import datetime
import json
import os
import sys
import time

from wherehows.common.writers import FileWriter
from wherehows.common.schemas import DatasetSchemaRecord, DatasetFieldRecord
from wherehows.common import Constant
from org.slf4j import LoggerFactory

import FileUtil


class TeradataTransform:
  def __init__(self):
    self.logger = LoggerFactory.getLogger('jython script : ' + self.__class__.__name__)

  def transform(self, input, td_metadata, td_field_metadata):
    '''
    convert from json to csv
    :param input: input json file
    :param td_metadata: output data file for teradata metadata
    :param td_field_metadata: output data file for teradata field metadata
    :return:
    '''
    f_json = open(input)
    data = json.load(f_json)
    f_json.close()

    schema_file_writer = FileWriter(td_metadata)
    field_file_writer = FileWriter(td_field_metadata)

    for d in data:
      i = 0
      for k in d.keys():
        if k not in ['tables', 'views']:
          continue
        self.logger.info("%s %4d %s" % (datetime.datetime.now().strftime("%H:%M:%S"), len(d[k]), k))
        for t in d[k]:
          self.logger.info("%4d %s" % (i, t['name']))
          if t['name'] == 'HDFStoTD_2464_ERR_1':
            continue
          i += 1
          output = {}
          prop_json = {}
          output['name'] = t['name']
          output['original_name'] = t['original_name']

          prop_json["createTime"] = t["createTime"] if t.has_key("createTime") else None
          prop_json["lastAlterTime"] = t["lastAlterTime"] if t.has_key("lastAlterTime") else None
          prop_json["lastAccessTime"] = t["lastAccessTime"] if t.has_key("lastAccessTime") else None
          prop_json["accessCount"] = t["accessCount"] if t.has_key("accessCount") else None
          prop_json["sizeInMbytes"] = t["sizeInMbytes"] if t.has_key("sizeInMbytes") else None
          if "type" in t:
            prop_json["storage_type"] = t["type"]
          if "partition" in t:
            prop_json["partition"] = t["partition"]
          if "partitions" in t:
            prop_json["partitions"] = t["partitions"]
          if "hashKey" in t:
            prop_json["hashKey"] = t["hashKey"]
          if "indices" in t:
            prop_json["indices"] = t["indices"]
          if "referenceTables" in t:
            prop_json["referenceTables"] = t["referenceTables"]
          if "viewSqlText" in t:
            prop_json["viewSqlText"] = t["viewSqlText"]

          output['fields'] = []
          flds = {}
          field_detail_list = []
          sort_id = 0
          for c in t['columns']:
            # output['fields'].append(
            #                    { 'name' : t['name'].encode('latin-1'),
            #                      'type' : None if c['data_type'] is None else c['data_type'].encode('latin-1'),
            #                      'attributes_json' : c}
            #                output['fields'][c['name'].encode('latin-1')].append({ "doc" : "", "type" : [None if c['data_type'] is None else c['data_type'].encode('latin-1')]})
            sort_id += 1
            output['fields'].append({"name": c['name'], "doc": '', "type": c['dataType'] if c['dataType'] else None,
                                     "nullable": c['nullable'], "maxByteLength": c['maxByteLength'],
                                     "format": c['columnFormat'] if c.has_key('columnFormat') else None,
                                     "accessCount": c['accessCount'] if c.has_key('accessCount') else None,
                                     "lastAccessTime": c['lastAccessTime'] if c.has_key("lastAccessTime") else None})

            flds[c['name']] = {'type': c['dataType'], "maxByteLength": c['maxByteLength']}

            field_detail_list.append(
              ["teradata:///%s/%s" % (d['database'], output['name']), str(sort_id), '0', '', c['name'], '',
               c['dataType'] if 'dataType' in c and c['dataType'] is not None else '',
               str(c['maxByteLength']) if 'maxByteLength' in c else '0',
               str(c['precision']) if 'precision' in c and c['precision'] is not None else '',
               str(c['scale']) if 'scale' in c and c['scale'] is not None else '',
               c['nullable'] if 'nullable' in c and c['nullable'] is not None else 'Y', '', '', '', '', '', '', ''])

          dataset_scehma_record = DatasetSchemaRecord(output['name'], json.dumps(output), json.dumps(prop_json),
                                                      json.dumps(flds),
                                                      "teradata:///%s/%s" % (d['database'], output['name']), 'Teradata',
                                                      output['original_name'],
                                                      (self.convert_timestamp(t["createTime"]) if t.has_key("createTime") else None),
                                                      (self.convert_timestamp(t["lastAlterTime"]) if t.has_key("lastAlterTime") else None))
          schema_file_writer.append(dataset_scehma_record)

          for fields in field_detail_list:
            field_record = DatasetFieldRecord(fields)
            field_file_writer.append(field_record)

        schema_file_writer.flush()
        field_file_writer.flush()
        self.logger.info("%20s contains %6d %s" % (d['database'], i, k))

    schema_file_writer.close()
    field_file_writer.close()

  def convert_timestamp(self, time_string):
    return int(time.mktime(time.strptime(time_string, "%Y-%m-%d %H:%M:%S")))


if __name__ == "__main__":
  args = sys.argv[1]
  t = TeradataTransform()
  t.log_file = args['teradata.log']

  temp_dir = FileUtil.etl_temp_dir(args, "TERADATA")
  input = os.path.join(temp_dir, args[Constant.TD_SCHEMA_OUTPUT_KEY])
  td_metadata = os.path.join(temp_dir, args[Constant.TD_METADATA_KEY])
  td_field_metadata = os.path.join(temp_dir, args[Constant.TD_FIELD_METADATA_KEY])

  t.transform(input, td_metadata, td_field_metadata)