我正在尝试使用hadoop、flume和hive进行twitter情绪分析。使用tweets.sql文件(使用配置单元)创建tweet表时,出现此错误。命令:
hive -f tweets.sql
错误
which: no hbase in (/usr/local/sbin:/usr/sbin:/sbin:/usr/local/bin:/usr/bin:/bin:/usr/local/jdk1.8.0_111/bin:/hadoop/Flume/bin:/apache-maven-3.3.9/bin:/hadoop/sbin:/hadoop/bin:/usr/lib/hive/bin:/usr/lib/derby/bin:/root/bin:/usr/local/jdk1.8.0_111/bin:/hadoop/Flume/bin:/apache-maven-3.3.9/bin:/hadoop/sbin:/hadoop/bin:/usr/lib/hive/bin:/usr/lib/derby/bin)
Logging initialized using configuration in jar:file:/usr/lib/hive/lib/hive-common-2.1.0.jar!/hive-log4j2.properties Async: true
FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask. Cannot validate serde: org.apache.hive.hcatalog.data.JsonSerDe
我还向hive lib文件夹和mapreduce lib文件夹添加了json-serde-1.3.8-snapshot-jar-with-dependencies,但没有效果。
推文.sql
--create the tweets_raw table containing the records as received from Twitter
SET hive.support.sql11.reserved.keywords=false;
CREATE EXTERNAL TABLE Mytweets_raw (
id BIGINT,
created_at STRING,
source STRING,
favorited BOOLEAN,
retweet_count INT,
retweeted_status STRUCT<
text:STRING,
user:STRUCT<screen_name:STRING,name:STRING>>,
entities STRUCT<
urls:ARRAY<STRUCT<expanded_url:STRING>>,
user_mentions:ARRAY<STRUCT<screen_name:STRING,name:STRING>>,
hashtags:ARRAY<STRUCT<text:STRING>>>,
text STRING,
user STRUCT<
screen_name:STRING,
name:STRING,
friends_count:INT,
followers_count:INT,
statuses_count:INT,
verified:BOOLEAN,
utc_offset:INT,
time_zone:STRING>,
in_reply_to_screen_name STRING
)
ROW FORMAT SERDE 'org.apache.hive.hcatalog.data.JsonSerDe'
LOCATION '/user/flume/tweets';
-- create sentiment dictionary
CREATE EXTERNAL TABLE dictionary (
type string,
length int,
word string,
pos string,
stemmed string,
polarity string
)
ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
STORED AS TEXTFILE
LOCATION '/data/dictionary';
-- loading data to the table dictionary
load data inpath 'data/dictionary/dictionary.tsv' INTO TABLE dictionary;
CREATE EXTERNAL TABLE time_zone_map (
time_zone string,
country string
)
ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
STORED AS TEXTFILE
LOCATION '/data/time_zone_map';
-- loading data to the table time_zone_map
load data inpath 'data/time_zone_map/time_zone_map.tsv' INTO TABLE time_zone_map;
-- Clean up tweets
CREATE VIEW tweets_simple AS
SELECT
id,
cast ( from_unixtime( unix_timestamp(concat( '2014 ', substring(created_at,5,15)), 'yyyy MMM dd hh:mm:ss')) as timestamp) ts,
text,
user.time_zone
FROM Mytweets_raw
;
CREATE VIEW tweets_clean AS
SELECT
id,
ts,
text,
m.country
FROM tweets_simple t LEFT OUTER JOIN time_zone_map m ON t.time_zone = m.time_zone;
-- Compute sentiment
create view l1 as select id, words from Mytweets_raw lateral view explode(sentences(lower(text))) dummy as words;
create view l2 as select id, word from l1 lateral view explode( words ) dummy as word ;
create view l3 as select
id,
l2.word,
case d.polarity
when 'negative' then -1
when 'positive' then 1
else 0 end as polarity
from l2 left outer join dictionary d on l2.word = d.word;
create table tweets_sentiment as select
id,
case
when sum( polarity ) > 0 then 'positive'
when sum( polarity ) < 0 then 'negative'
else 'neutral' end as sentiment
from l3 group by id;
-- put everything back together and re-name sentiments...
CREATE TABLE tweetsbi
AS
SELECT
t.*,
s.sentiment
FROM tweets_clean t LEFT OUTER JOIN tweets_sentiment s on t.id = s.id;
-- data with tweet counts.....
CREATE TABLE tweetsbiaggr
AS
SELECT
country,sentiment, count(sentiment) as tweet_count
FROM tweetsbi
group by country,sentiment;
-- store data for analysis......
CREATE VIEW A as select country,tweet_count as positive_response from tweetsbiaggr where sentiment='positive';
CREATE VIEW B as select country,tweet_count as negative_response from tweetsbiaggr where sentiment='negative';
CREATE VIEW C as select country,tweet_count as neutral_response from tweetsbiaggr where sentiment='neutral';
CREATE TABLE tweetcompare as select A.*,B.negative_response as negative_response,C.neutral_response as neutral_response from A join B on A.country= B.country join C on B.country=C.country;
-- permission to show data in Excel sheet for analysis ....
grant SELECT ON TABLE tweetcompare to user hue;
grant SELECT ON TABLE tweetcompare to user root;
-- for Tableau or Excel
-- UDAF sentiscore = sum(sentiment)*50 / count(sentiment)
-- context n-gram made readable
巴什尔
export JAVA_HOME=/usr/local/jdk1.8.0_111
export PATH=$PATH:$JAVA_HOME/bin
export HADOOP_HOME=/hadoop
export FLUME_HOME=/hadoop/Flume
export FLUME_CONF_DIR=$FLUME_HOME/conf
export PATH=$PATH:$FLUME_HOME/bin
export CLASSPATH=$CLASSPATH:/FLUME_HOME/lib/*
export MAVEN_HOME=/apache-maven-3.3.9
export PATH=$PATH:$MAVEN_HOME/bin
export HADOOP_INSTALL=$HADOOP_HOME
export HADOOP_MAPRED_HOME=$HADOOP_HOME
export HADOOP_COMMON_HOME=$HADOOP_HOME
export HADOOP_HDFS_HOME=$HADOOP_HOME
export YARN_HOME=$HADOOP_HOME
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native
export PATH=$PATH:$HADOOP_HOME/sbin:$HADOOP_HOME/bin
export HIVE_HOME=/usr/lib/hive
export PATH=$PATH:$HIVE_HOME/bin
export CLASSPATH=$CLASSPATH:/HIVE_HOME/lib/*
export DERBY_HOME=/usr/lib/derby
export PATH=$PATH:$DERBY_HOME/bin
请告诉我怎么修这个。
暂无答案!
目前还没有任何答案,快来回答吧!