Everytime I am trying to select in IMPALA a DATE type field from a table created in HIVE I get the AnalysisException: Unsupported type 'DATE'.
Are there any workarounds?
UPDATE this is an example of a create table schema from hive and an impala query
Schema:
CREATE TABLE myschema.mytable(day_dt date,
event string)
PARTITIONED BY (day_id int)
STORED AS INPUTFORMAT
'org.apache.hadoop.mapred.TextInputFormat'
OUTPUTFORMAT
'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
Impala query
select b.day_dt
from myschema.mytable b;
Impala doesn't have a DATE datatype, whereas Hive has. You will get AnalysisException: Unsupported type 'DATE' when you access it from Impala. A quick fix would be to create a string column of that date value in Hive and access it in whichever way you want from Impala.
If you're storing as strings, it may work to create a new external hive table that points to the same HDFS location as the existing table, but with the schema having day_dt with datatype STRING instead of DATE.
This is a true workaround, it may only suit some use cases, and you'd at least need to do "MSCK REPAIR" on the external hive table whenever a new partition is added.
Related
I have created a table employee_orc which is orc format with snappy compression.
create table employee_orc(emp_id string, name string)
row format delimited fields terminated by '\t' stored as orc tblproperties("orc.compress"="SNAPPY");
I have uploaded data into the table using the insert statement.
employee_orc table has 1000 records.
When I run the below query, it shows all the records
select * from employee_orc;
But when run the below query, it shows zero results even though the records exist.
select * from employee_orc where emp_id = "EMP456";
Why I am unable to retrieve a single record from the employee_orc table?
The record does not exist. You may think they are the same because they look the same, but there is some difference. One possibility are spaces at the beginning or end of the string. For this, you can use like:
where emp_id like '%EMP456%'
This might help you.
On my part, I don't understand why you want to specify a delimiter in ORC. Are you confusing CSV and ORC or external vs managed ?
I advice you to create your table differently
create table employee_orc(emp_id string, name string)
stored as ORC
TBLPROPERTIES (
"orc.compress"="ZLIB");
I've have a CSV files which contain date and timestamp values in the below formats. Eg:
Col1|col2
01JAN2019|01JAN2019:17:34:41
But when I define Col1 as Date and Col2 as Timestamp in my create statement, the Hive tables simply returns NULL when I query.
CREATE EXTERNAL TABLE IF NOT EXISTS my_schema.my_table
(Col1 date,
Col2 timestamp)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ‘|’
STORED AS TEXTFILE
LOCATION 'my_path';
Instead, if I define the data types as simply string then it works. But that's not how I want my tables to be.
I want the table to be able to read the incoming data in correct type. How can I achieve this? Is it possible to define the expected data format of the incoming data with the CREATE statement itself?
Can someone please help?
As of Hive 1.2.0 it is possible to provide additional SerDe property "timestamp.formats". See this Jira for more details: HIVE-9298
ALTER TABLE timestamp_formats SET SERDEPROPERTIES ("timestamp.formats"="ddMMMyyyy:HH:mm:ss");
I have an export job from Datameer going through to HIVE. The issue is that we were told that HIVE converts Date columns to string. I am feeding the data from HIVE to Tableau and the issue is that the Date column being converted to string is completely throwing off my data.
I am looking to convert/alter my existing column "Posting_Date" from String to Date... HIVE is based off a Teradata interface so I am trying to find a command which will let me convert this column back to Date format..
I tried the following:
ALTER table Database.Table1
ADD posting_date date(4)
While trying to load data in a Hive table I encountered a behavior that looks strange to me. My data is made up of JSON objects loaded as records in a table called twitter_test containing a single column named "json".
Now I want to extract three fields from each JSON and build a new table called "my_twitter". I thus issue the command
CREATE TABLE my_twitter AS SELECT regexp_replace(get_json_object(t.json, '$.body\[0]'), '\n', '') as text, get_json_object(t.json, '$.publishingdate\[0]') as created_at, get_json_object(t.json, '$.author_screen_name\[0]') as author from twitter_test AS t;
The result is a table with three columns that contains no data. However, if I run the SELECT command alone it returns data as expected.
By trial and error I found out that i need to add LIMIT x at the end of the query for data to be inserted in the new table. The question is: why?
Furthermore, seems strange that I need to know in advance the number x of rows returned by the SELECT statement for the CREATE to work correctly. Is there any workaround?
You could create a table on this json data using the JSON serde which would parse the json objects and then you could easily select each individual columns easily.
Find below a sample hive DDL for creating a json table using json serde
CREATE EXTERNAL TABLE `json_table`(
A string
,B string
)
ROW FORMAT SERDE
'org.apache.hive.hcatalog.data.JsonSerDe'
STORED AS INPUTFORMAT
'org.apache.hadoop.mapred.TextInputFormat'
OUTPUTFORMAT
'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION
'PATH'
I have a Parquet file (created by Drill) that I'm trying to read in Hive as an external table. The data types are copied one-to-one (i.e. INTEGER -> INT, BIGINT -> BIGINT, DOUBLE -> DOUBLE, TIMESTAMP -> TIMESTAMP, CHARACTER VARYING -> STRING). There are no complex types.
Drill has no problem querying the file it created, but Hive does not like it:
CREATE EXTERNAL TABLE my_table
(
<col> <data_type>
)
STORED AS PARQUET
LOCATION '<hdfs_location>';
I can execute SELECT COUNT(*) FROM my_table and get the correct number of rows back, but when I ask for the first row it says:
Error: java.io.IOException: org.apache.hadoop.hive.ql.metadata.HiveException: java.lang.ClassCastException: org.apache.hadoop.io.IntWritable cannot be cast to org.apache.hadoop.io.LongWritable (state=,code=0)
I'm not sure why it complains because I use integers and big integers, none of which I assume are stored as longs. Moreover, I would assume that an integer can be cast to a long. Is there a known workaround?
its just because of your data.
I was also facing same issue.
My data in the format of int and I have created external table as String.
Give appropriate datatypes in hive create statement.
Hive does not support certain data types e.g long - use bigint
Here is the 2-steps solution:
First, drop the Table
Drop TABLE if exists <TableName>
Second, recreate the Table, this time with 'bigint' instead of 'long'
Create external TABLE <TableName>
(
<col> bigint
)
Stored as Parquet
Location '<hdfs_location>';