Failed to properly load twitter avro data into hive table

I need your help!

I am trying a trivial exercise of fetching data from twitter and then uploading it to Hive for analysis. Although I can get data in HDFS using flume (using 1% Firehose Source) and also able to load data into Hive table.

But couldn't see all the columns I expected to be present in twitter data like user_location, user_description, user_friends_count, user_description, user_statuses_count. The schema derived from Avro contains only two columns and a column body.

Below are the steps I took:

1) create a marker with below conf:

a1.sources = r1
a1.sinks = k1
a1.channels = c1

# Describe/configure the source
a1.sources.r1.type =org.apache.flume.source.twitter.TwitterSource
#a1.sources.r1.type = com.cloudera.flume.source.TwitterSource
a1.sources.r1.consumerKey =XXXXXXXXXXXXXXXXXXXXXXXXXXXX
a1.sources.r1.consumerSecret =XXXXXXXXXXXXXXXXXXXXXXXXXXXX
a1.sources.r1.accessToken =XXXXXXXXXXXXXXXXXXXXXXXXXXXX
a1.sources.r1.accessTokenSecret =XXXXXXXXXXXXXXXXXXXXXXXXXXXX
a1.sources.r1.keywords = bigdata, healthcare, oozie


# Describe the sink
a1.sinks.k1.type = hdfs
a1.sinks.k1.hdfs.path = hdfs://192.168.192.128:8020/hdp/apps/2.2.0.0-2041/flume/twitter
a1.sinks.k1.hdfs.fileType = DataStream
a1.sinks.k1.hdfs.writeFormat = Text

a1.sinks.k1.hdfs.inUsePrefix = _
a1.sinks.k1.hdfs.fileSuffix = .avro
# added for invalid block size error
a1.sinks.k1.serializer = avro_event

#a1.sinks.k1.deserializer.schemaType = LITERAL
# added for  exception java.io.IOException:org.apache.avro.AvroTypeException: Found Event, expecting Doc
#a1.sinks.k1.serializer.compressionCodec = snappy

a1.sinks.k1.hdfs.batchSize = 1000
a1.sinks.k1.hdfs.rollSize = 67108864
a1.sinks.k1.hdfs.rollCount = 0
a1.sinks.k1.hdfs.rollInterval = 30


# Use a channel which buffers events in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 1000

# Bind the source and sink to the channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

      

2) Output the schema from the avro datafile, I don't know why the schema obtained from the avro datafile only has two columns and a column body:

java -jar avro-tools-1.7.7.jar getschema FlumeData.14315982                             30978.avro
{
  "type" : "record",
  "name" : "Event",
  "fields" : [ {
    "name" : "headers",
    "type" : {
      "type" : "map",
      "values" : "string"
    }
  }, {
    "name" : "body",
    "type" : "bytes"
  } ]
}

      

3) Start the above agent and get data in HDFS, find out avro data schema and create Hive table like:

    CREATE EXTERNAL TABLE TwitterData
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.avro.AvroSerDe'
WITH SERDEPROPERTIES ('avro.schema.literal'='
{
  "type" : "record",
  "name" : "Event",
  "fields" : [ {
    "name" : "headers",
    "type" : {
      "type" : "map",
      "values" : "string"
    }
  }, {
    "name" : "body",
    "type" : "bytes"
  } ]
}

')
STORED AS
INPUTFORMAT 'org.apache.hadoop.hive.ql.io.avro.AvroContainerInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.avro.AvroContainerOutputFormat'
LOCATION 'hdfs://192.168.192.128:8020/hdp/apps/2.2.0.0-2041/flume/twitter'
;

      

4) Describe the table of the hive:

hive> describe  twitterdata;
OK
headers                 map<string,string>      from deserializer
body                    binary                  from deserializer
Time taken: 0.472 seconds, Fetched: 2 row(s)

      

5) Query the table: When I query the table, I see binary data in the "body" column and the actual schema information in the "header" column.

select * from twitterdata limit 1;
OK

{"type":"record","name":"Doc","doc":"adoc","fields":[{"name":"id","type":"string"},{"name":"user_friends_count","type":["int","null"]},{"name":"user_location","type":["string","null"]},{"name":"user_description","type":["string","null"]},{"name":"user_statuses_count","type":["int","null"]},{"name":"user_followers_count","type":["int","null"]},{"name":"user_name","type":["string","null"]},{"name":"user_screen_name","type":["string","null"]},{"name":"created_at","type":["string","null"]},{"name":"text","type":["string","null"]},{"name":"retweet_count","type":["long","null"]},{"name":"retweeted","type":["boolean","null"]},{"name":"in_reply_to_user_id","type":["long","null"]},{"name":"source","type":["string","null"]},{"name":"in_reply_to_status_id","type":["long","null"]},{"name":"media_url_https","type":["string","null"]},{"name":"expanded_url","type":["string","null"]}]} 1|$   )]'  G $598792495703543808 Bあいたぁぁぁぁぁぁぁ! ~ ゆっけ0725Yukken(2015-05-14T10:10:30Z<ん?なんか意味違うわ <a href="http://twitter.com/download/iphone" rel="nofollow">Twitter for iPhone</a> 1|$   )]'  
Time taken: 2.24 seconds, Fetched: 1 row(s)

      

How to create a hive table with all columns in a real schema as shown in the "header" column. I mean all columns like user_location, user_description, user_friends_count, user_description, user_statuses_count?

Should the schema obtained from the avro data file contain more columns?

Is there a problem with the flume-avro source I used in the flume agent (org.apache.flume.source.twitter.TwitterSource)?

Thanks for reading ..

Thanks Farrukh, I made that the error was the configuration "a1.sinks.k1.serializer = avro_event", I changed it to "a1.sinks.k1.serializer = text" and I was able to load the data into the Hive. But now the problem is fetching data from Hive, while doing this I get the following error:

        hive> describe twitterdata_09062015;
    OK
    id                      string                  from deserializer
    user_friends_count      int                     from deserializer
    user_location           string                  from deserializer
    user_description        string                  from deserializer
    user_statuses_count     int                     from deserializer
    user_followers_count    int                     from deserializer
    user_name               string                  from deserializer
    user_screen_name        string                  from deserializer
    created_at              string                  from deserializer
    text                    string                  from deserializer
    retweet_count           bigint                  from deserializer
    retweeted               boolean                 from deserializer
    in_reply_to_user_id     bigint                  from deserializer
    source                  string                  from deserializer
    in_reply_to_status_id   bigint                  from deserializer
    media_url_https         string                  from deserializer
    expanded_url            string                  from deserializer


select count(1) as num_rows from TwitterData_09062015; 
    Query ID = root_20150609130404_10ef21db-705a-4e94-92b7-eaa58226ee2e 
    Total jobs = 1 
    Launching Job 1 out of 1 
    Number of reduce tasks determined at compile time: 1 
    In order to change the average load for a reducer (in bytes): 
    set hive.exec.reducers.bytes.per.reducer=<number> 
    In order to limit the maximum number of reducers: 
    set hive.exec.reducers.max=<number> 
    In order to set a constant number of reducers: 
    set mapreduce.job.reduces=<number> 
    Starting Job = job_1433857038961_0003, Tracking URL = http://sandbox.hortonworks.com:8088/proxy/application_14338570 38961_0003/ 
    Kill Command = /usr/hdp/2.2.0.0-2041/hadoop/bin/hadoop job -kill job_1433857038961_0003 
    Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1 
    * 13:04:36,856 Stage-1 map = 0%, reduce = 0%

    * 13:05:09,576 Stage-1 map = 100%, reduce = 100%

    Ended Job = job_1433857038961_0003 with errors 
    Error during job, obtaining debugging information... 
    Examining task ID: task_1433857038961_0003_m_000000 (and more) from job job_1433857038961_0003

    Task with the most failures(4):

    Task ID: 
    task_1433857038961_0003_m_000000

    URL: 
    http://sandbox.hortonworks.com:8088/taskdetails.jsp?jobid=job_1433857038961_0003&tipid=task_1433857038961_0003_m_0 00000

    Diagnostic Messages for this Task: 
    Error: java.io.IOException: java.io.IOException: org.apache.avro.AvroRuntimeException: java.io.IOException: Block si ze invalid or too large for this implementation: -40 
    at org.apache.hadoop.hive.io.HiveIOExceptionHandlerChain.handleRecordReaderNextException(HiveIOExceptionHand lerChain.java:121) 

      

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Here is the step-by-step that was used to download the tweets and upload them to the hive.

Felt-tip pen

##TwitterAgent for collecting Twitter data to Hadoop HDFS #####

TwitterAgent.sources = Twitter
TwitterAgent.channels = FileChannel
TwitterAgent.sinks = HDFS


TwitterAgent.sources.Twitter.type = org.apache.flume.source.twitter.TwitterSource
TwitterAgent.sources.Twitter.channels = FileChannel
TwitterAgent.sources.Twitter.consumerKey = *************
TwitterAgent.sources.Twitter.consumerSecret = **********
TwitterAgent.sources.Twitter.accessToken = ************
TwitterAgent.sources.Twitter.accessTokenSecret = ***********

TwitterAgent.sources.Twitter.maxBatchSize = 50000
TwitterAgent.sources.Twitter.maxBatchDurationMillis = 100000

TwitterAgent.sources.Twitter.keywords = Apache, Hadoop, Mapreduce, hadooptutorial, Hive, Hbase, MySql

TwitterAgent.sinks.HDFS.channel = FileChannel
TwitterAgent.sinks.HDFS.type = hdfs
TwitterAgent.sinks.HDFS.hdfs.path = hdfs://nn1.itbeams.com:9000/user/flume/tweets/avrotweets
TwitterAgent.sinks.HDFS.hdfs.fileType = DataStream
# you do not need to mentioned avro format here. just mention Text
TwitterAgent.sinks.HDFS.hdfs.writeFormat = Text
TwitterAgent.sinks.HDFS.hdfs.batchSize = 200000
TwitterAgent.sinks.HDFS.hdfs.rollSize = 0
TwitterAgent.sinks.HDFS.hdfs.rollCount = 2000000

TwitterAgent.channels.FileChannel.type = file
TwitterAgent.channels.FileChannel.checkpointDir = /var/log/flume/checkpoint/
TwitterAgent.channels.FileChannel.dataDirs = /var/log/flume/data/

      

I have created an avro schematic in the avsc file. After you create, place this file in your user folder, for example / user / youruser /.

{"type":"record",
 "name":"Doc",
 "doc":"adoc",
 "fields":[{"name":"id","type":"string"},
           {"name":"user_friends_count","type":["int","null"]},
           {"name":"user_location","type":["string","null"]},
           {"name":"user_description","type":["string","null"]},
           {"name":"user_statuses_count","type":["int","null"]},
           {"name":"user_followers_count","type":["int","null"]},
           {"name":"user_name","type":["string","null"]},
           {"name":"user_screen_name","type":["string","null"]},
           {"name":"created_at","type":["string","null"]},
           {"name":"text","type":["string","null"]},
           {"name":"retweet_count","type":["long","null"]},
           {"name":"retweeted","type":["boolean","null"]},
           {"name":"in_reply_to_user_id","type":["long","null"]},
           {"name":"source","type":["string","null"]},
           {"name":"in_reply_to_status_id","type":["long","null"]},
           {"name":"media_url_https","type":["string","null"]},
           {"name":"expanded_url","type":["string","null"]}

      



Downloaded tweets in the beehive table. If you save the code in an hql file, that would be great.

CREATE TABLE tweetsavro
  ROW FORMAT SERDE
     'org.apache.hadoop.hive.serde2.avro.AvroSerDe'
  STORED AS INPUTFORMAT
     'org.apache.hadoop.hive.ql.io.avro.AvroContainerInputFormat'
  OUTPUTFORMAT
     'org.apache.hadoop.hive.ql.io.avro.AvroContainerOutputFormat'
  TBLPROPERTIES ('avro.schema.url'='hdfs:///user/youruser/examples/schema/twitteravroschema.avsc') ;

LOAD DATA INPATH '/user/flume/tweets/avrotweets/FlumeData.*' OVERWRITE INTO TABLE tweetsavro;

      

tweetsavro table in beehive

hive> describe tweetsavro;
OK
id                      string                  from deserializer
user_friends_count      int                     from deserializer
user_location           string                  from deserializer
user_description        string                  from deserializer
user_statuses_count     int                     from deserializer
user_followers_count    int                     from deserializer
user_name               string                  from deserializer
user_screen_name        string                  from deserializer
created_at              string                  from deserializer
text                    string                  from deserializer
retweet_count           bigint                  from deserializer
retweeted               boolean                 from deserializer
in_reply_to_user_id     bigint                  from deserializer
source                  string                  from deserializer
in_reply_to_status_id   bigint                  from deserializer
media_url_https         string                  from deserializer
expanded_url            string                  from deserializer
Time taken: 0.6 seconds, Fetched: 17 row(s)

      

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