I use flume to write data to hdfs,path like /hive/logs/dt=20151002.Then,i use hive to select data,but the count of response is always 0.
Here is my create table sql,CREATE EXTERNAL TABLE IF NOT EXISTS test (id STRING) partitioned by (dt string) ROW FORMAT DELIMITED fields terminated by '\t' lines terminated by '\n' STORED AS TEXTFILE LOCATION '/hive/logs'
Here is my select sql,select count(*) from test
It seems that you are not registering partition in hive meta-store.
Although partition is present in hdfs path,Hive won't know it if its not registered in meta store. To register it you can do the following:
ALTER TABLE test ADD PARTITION (dt='20151002') location '/hive/logs/dt=20151002';
Related
I needed to create huge test data in hive table. I tried following commands but it only inserts one partition data at a time.
connect to beeline:
beeline --force=true -u 'jdbc:hive2://<host>:<port>/<hive database name>;ssl=true;user=<username>;password=<pw>'
create partitioned table :
CREATE TABLE p101(
Name string,
Age string)
PARTITIONED BY(fi string)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ',';
I have created ins.csv file with data and copy it to hdfs location, its data is as follows.
Name,Age
aaa,33
bbb,22
ccc,55
then I tried to load same file for multiple partition ids with following command
LOAD DATA INPATH 'hdfs_path/ins.csv' INTO TABLE p101 PARTITION(fi=1,fi=2,fi=3,fi=4,fi=5);
but it loads record only for partitionID=5.
You can only specify one partition for each insert into.
What you can do in order to have different partitions is add it into your csv file like this:
Name,Age,fi
aaa,33,1
bbb,22,2
ccc,55,3
Hive will automatically know that this is the partition.
LOAD DATA INPATH 'hdfs_path/ins.csv' INTO TABLE tmp.p101;
I have the following file on HDFS:
I create the structure of the external table in Hive:
CREATE EXTERNAL TABLE google_analytics(
`session` INT)
PARTITIONED BY (date_string string)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
LOCATION '/flumania/google_analytics';
ALTER TABLE google_analytics ADD PARTITION (date_string = '2016-09-06') LOCATION '/flumania/google_analytics';
After that, the table structure is created in Hive but I cannot see any data:
Since it's an external table, data insertion should be done automatically, right?
your file should be in this sequence.
int,string
here you file contents are in below sequence
string, int
change your file to below.
86,"2016-08-20"
78,"2016-08-21"
It should work.
Also it is not recommended to use keywords as column names (date);
I think the problem was with the alter table command. The code below solved my problem:
CREATE EXTERNAL TABLE google_analytics(
`session` INT)
PARTITIONED BY (date_string string)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
LOCATION '/flumania/google_analytics/';
ALTER TABLE google_analytics ADD PARTITION (date_string = '2016-09-06');
After these two steps, if you have a date_string=2016-09-06 subfolder with a csv file corresponding to the structure of the table, data will be automatically loaded and you can already use select queries to see the data.
Solved!
I have a map reduce job, that already writes out record to hdfs using hive partition naming convention.
eg
/user/test/generated/code=1/channel=A
/user/test/generated/code=1/channel=B
After I create an external table, it does not see the partition.
create external table test_1 ( id string, name string ) partitioned by
(code string, channel string) STORED AS PARQUET LOCATION
'/user/test/generated'
Even with the alter command
alter table test_1 ADD PARTITION (code = '1', channel = 'A')
, it does not see the partition or record,
because
select * from test_1 limit 1 produces 0 result.
If I use empty location when I create external table, and then use
load data inpath ...
then it works. But the issue is there is too many partitions for the load data inpath to work.
Is there a way to make hive recognize the partition automatically (without doing insert query)?
Using msck, it seems to be working. But I had to exit the hive session, and connect again.
MSCK REPAIR TABLE test_1
I have data stored in S3 like:
/bucket/date=20140701/file1
/bucket/date=20140701/file2
...
/bucket/date=20140701/fileN
/bucket/date=20140702/file1
/bucket/date=20140702/file2
...
/bucket/date=20140702/fileN
...
My understanding is that if I pull in that data via Hive, it will automatically interpret date as a partition. My table creation looks like:
CREATE EXTERNAL TABLE search_input(
col 1 STRING,
col 2 STRING,
...
)
PARTITIONED BY(date STRING)
ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
LINES TERMINATED BY '\n'
LOCATION 's3n://bucket/';
However Hive doesn't recognize any data. Any queries I run return with 0 results. If I instead just grab one of the dates via:
CREATE EXTERNAL TABLE search_input_20140701(
col 1 STRING,
col 2 STRING,
...
)
ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
LINES TERMINATED BY '\n'
LOCATION 's3n://bucket/date=20140701';
I can query data just fine.
Why doesn't Hive recognize the nested directories with the "date=date_str" partition?
Is there a better way to have Hive run a query over multiple sub-directories and slice it based on a datetime string?
In order to get this to work I had to do 2 things:
Enable recursive directory support:
SET mapred.input.dir.recursive=true;
SET hive.mapred.supports.subdirectories=true;
For some reason it would still not recognize my partitions so I had to recover them via:
ALTER TABLE search_input RECOVER PARTITIONS;
You can use:
SHOW PARTITIONS table;
to check and see that they've been recovered.
I had faced the same issue and realized that hive does not have partitions metadata with it. So we need to add that metadata using ALTER TABLE ADD PARTITION query. It becomes tedious, if you have few hundred partitions to create same queries with different values.
ALTER TABLE <table name> ADD PARTITION(<partitioned column name>=<partition value>);
Once you run above query for all available partitions. You should see the results in hive queries.
I've created a Hive Table through an Elastic MapReduce interactive session and populated it from a CSV file like this:
CREATE TABLE csvimport(id BIGINT, time STRING, log STRING)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\t';
LOAD DATA LOCAL INPATH '/home/hadoop/file.csv' OVERWRITE INTO TABLE csvimport;
I now want to store the Hive table in a S3 bucket so the table is preserved once I terminate the MapReduce instance.
Does anyone know how to do this?
Yes you have to export and import your data at the start and end of your hive session
To do this you need to create a table that is mapped onto S3 bucket and directory
CREATE TABLE csvexport (
id BIGINT, time STRING, log STRING
)
row format delimited fields terminated by ','
lines terminated by '\n'
STORED AS TEXTFILE
LOCATION 's3n://bucket/directory/';
Insert data into s3 table and when the insert is complete the directory will have a csv file
INSERT OVERWRITE TABLE csvexport
select id, time, log
from csvimport;
Your table is now preserved and when you create a new hive instance you can reimport your data
Your table can be stored in a few different formats depending on where you want to use it.
Above Query needs to use EXTERNAL keyword, i.e:
CREATE EXTERNAL TABLE csvexport ( id BIGINT, time STRING, log STRING )
row format delimited fields terminated by ',' lines terminated by '\n'
STORED AS TEXTFILE LOCATION 's3n://bucket/directory/';
INSERT OVERWRITE TABLE csvexport select id, time, log from csvimport;
An another alternative is to use the query
INSERT OVERWRITE DIRECTORY 's3n://bucket/directory/' select id, time, log from csvimport;
the table is stored in the S3 directory with HIVE default delimiters.
If you could access aws console and have the "Access Key Id" and "Secret Access Key" for your account
You can try this too..
CREATE TABLE csvexport(id BIGINT, time STRING, log STRING)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\t'
LOCATION 's3n://"access id":"secret key"#bucket/folder/path';
Now insert the data as other stated above..
INSERT OVERWRITE TABLE csvexport select id, time, log from csvimport;