Change Hive External Table Column names to upper case and add new columns - hadoop

I have an external table for example dump_table, which is partitioned over year, month and day. If i run show create table dump_table i get the following:
CREATE EXTERNAL TABLE `dump_table`
(
`col_name` double,
`col_name_2` timestamp
)
PARTITIONED BY (
`year` int,
`month` int,
`day` int)
CLUSTERED BY (
someid)
INTO 32 BUCKETS
ROW FORMAT SERDE
'org.apache.hadoop.hive.ql.io.orc.OrcSerde'
STORED AS INPUTFORMAT
'org.apache.hadoop.hive.ql.io.orc.OrcInputFormat'
OUTPUTFORMAT
'org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat'
LOCATION
'hdfs://somecluster/test.db/dump_table'
TBLPROPERTIES (
'orc.compression'='SNAPPY',
'transient_lastDdlTime'='1564476840')
I have to change its columns to upper case and also add new columns, so it will become something like:
CREATE EXTERNAL TABLE `dump_table_2`
(
`COL_NAME` DOUBLE,
`COL_NAME_2` TIMESTAMP,
`NEW_COL` DOUBLE
)
PARTITIONED BY (
`year` int,
`month` int,
`day` int)
CLUSTERED BY (
someid)
Option:1
as an option I can run Change (DDL Reference here) to change column names and then add new columns to it. BUT the thing is that i do not have any backup for this table and it contains alot of data. If anything goes wrong I might loose data.
Can I create a new external table and migrate data, partition by partition from dump_table to dump_table_2 ? what will the query look like for this migration?
Is there any better way of achieving this use case? Please help

You can create new table dump_table_2 with new columns and load data using sql:
set hive.enforce.bucketing = true;
set hive.exec.dynamic.partition=true;
set hive.exec.dynamic.partition.mode=nonstrict;
insert overwrite table dump_table_2 partition (`year`, `month`, `day`)
select col1,
...
colN,
`year`, `month`, `day`
from dump_table_1 t --join other tables if necessary to calculate columns

Related

HIVE - Cannot partition a table: semantic exception failure

I'm not able to import data on partitioned table in Hive.
Here is how I create the table
CREATE TABLE IF NOT EXISTS title_ratings
(
tconst STRING,
averageRating DOUBLE,
numVotes INT
)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\t'
STORED AS TEXTFILE
TBLPROPERTIES("skip.header.line.count"="1");
And then I load the data into it : LOAD DATA INPATH '/title.ratings.tsv.gz' INTO TABLE eval_hive_db.title_ratings;
It works fine till here. Now I want to create a dynamic partitioned table. First of all, I setup theses params:
SET hive.exec.dynamic.partition=true;
SET hive.exec.dynamic.partition.mode=nonstrict;
I now create my partitioned table:
CREATE TABLE IF NOT EXISTS title_ratings_part
(
tconst STRING,
numVotes INT
)
PARTITIONED BY (averageRating DOUBLE)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\n'
STORED AS TEXTFILE;
insert into title_ratings_part partition(title_ratings) select tconst, averageRating, numVotes from title_ratings;
(I also tried with numVotes instead by the way)
And I receive this error: FAILED: ValidationFailureSemanticException eval_hive_db.title_ratings_part: Partition spec {title_ratings=null} contains non-partition columns
Someone can help me please?
Ideally, I want to partition my table by averageRating (less than 2, between 2 and 4, and greater than 4)
You can run this command to check if there are null values or not.
select count(averageRating) from title_ratings group by averageRating;
Now, if there are null values in this column then you will get the count, which you have to fill then apply partitioning again.
Partition column is stored as last column in a table so while inserting you need to maintain correct order in select statement.
Pls change order of columns in select.
insert into title_ratings_part partition(title_ratings)
Select
Tconst,
numVotes,
averageRating --orderwise this should always be last column
from title_ratings

Hive Partition By dynamic value in s3 file name

Assuming an S3 location with required data is of the form:
s3://stack-overflow-example/v1/
where each file title in v1/ is of the form
francesco_{YYY_DD_MM_HH}_totti.csv
and each csv file contains a unix timestamp as a column in each row.
Is it possible to create an external hive table partitioned by the {YYY_DD_MM_HH} in each file name without first creating an unpartitioned table?
I have tried the below:
create external table so_test
(
a int,
b int,
unixtimestamp string
)
PARTITIONED BY (
from_unixtime(CAST(ord/1000 as BIGINT), 'yyyy-MM-dd') string
)
LOCATION 's3://stack-overflow-example/v1'
but this fails.
An option that should work is creating an unpartitioned table like the below:
create external table so_test
(
a int,
b int,
unixtimestamp string
);
LOCATION 's3://stack-overflow-example/v1'
and then dynamically inserting into a partitioned table:
SET hive.exec.dynamic.partition=true;
SET hive.exec.dynamic.partition.mode=nonstrict;
create external table so_test_partitioned
(
a int,
b int,
unixtimestamp string
)
PARTITIONED BY (
datep string
)
LOCATION 's3://stack-overflow-example/v1';
INSERT OVERWRITE TABLE so_test_partitioned PARTITION (date)
select
a,
b,
unixtimestamp,
from_unixtime(CAST(ord/1000 as BIGINT), 'yyyy-MM-dd') as datep,
from so_test;
Is creating an unpartitioned table first the only way?

Alter hive table add or drop column

I have orc table in hive I want to drop column from this table
ALTER TABLE table_name drop col_name;
but I am getting the following exception
Error occurred executing hive query: OK FAILED: ParseException line 1:35 mismatched input 'user_id1' expecting PARTITION near 'drop' in drop partition statement
Can any one help me or provide any idea to do this? Note, I am using hive 0.14
You cannot drop column directly from a table using command ALTER TABLE table_name drop col_name;
The only way to drop column is using replace command. Lets say, I have a table emp with id, name and dept column. I want to drop id column of table emp. So provide all those columns which you want to be the part of table in replace columns clause. Below command will drop id column from emp table.
ALTER TABLE emp REPLACE COLUMNS( name string, dept string);
There is also a "dumb" way of achieving the end goal, is to create a new table without the column(s) not wanted. Using Hive's regex matching will make this rather easy.
Here is what I would do:
-- make a copy of the old table
ALTER TABLE table RENAME TO table_to_dump;
-- make the new table without the columns to be deleted
CREATE TABLE table AS
SELECT `(col_to_remove_1|col_to_remove_2)?+.+`
FROM table_to_dump;
-- dump the table
DROP TABLE table_to_dump;
If the table in question is not too big, this should work just well.
suppose you have an external table viz. organization.employee as: (not including TBLPROPERTIES)
hive> show create table organization.employee;
OK
CREATE EXTERNAL TABLE `organization.employee`(
`employee_id` bigint,
`employee_name` string,
`updated_by` string,
`updated_date` timestamp)
ROW FORMAT SERDE
'org.apache.hadoop.hive.ql.io.orc.OrcSerde'
STORED AS INPUTFORMAT
'org.apache.hadoop.hive.ql.io.orc.OrcInputFormat'
OUTPUTFORMAT
'org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat'
LOCATION
'hdfs://getnamenode/apps/hive/warehouse/organization.db/employee'
You want to remove updated_by, updated_date columns from the table. Follow these steps:
create a temp table replica of organization.employee as:
hive> create table organization.employee_temp as select * from organization.employee;
drop the main table organization.employee.
hive> drop table organization.employee;
remove the underlying data from HDFS (need to come out of hive shell)
[nameet#ip-80-108-1-111 myfile]$ hadoop fs -rm hdfs://getnamenode/apps/hive/warehouse/organization.db/employee/*
create the table with removed columns as required:
hive> CREATE EXTERNAL TABLE `organization.employee`(
`employee_id` bigint,
`employee_name` string)
ROW FORMAT SERDE
'org.apache.hadoop.hive.ql.io.orc.OrcSerde'
STORED AS INPUTFORMAT
'org.apache.hadoop.hive.ql.io.orc.OrcInputFormat'
OUTPUTFORMAT
'org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat'
LOCATION
'hdfs://getnamenode/apps/hive/warehouse/organization.db/employee'
insert the original records back into original table.
hive> insert into organization.employee
select employee_id, employee_name from organization.employee_temp;
finally drop the temp table created
hive> drop table organization.employee_temp;
ALTER TABLE emp REPLACE COLUMNS( name string, dept string);
Above statement can only change the schema of a table, not data.
A solution of this problem to copy data in a new table.
Insert <New Table> Select <selective columns> from <Old Table>
ALTER TABLE is not yet supported for non-native tables; i.e. what you get with CREATE TABLE when a STORED BY clause is specified.
check this https://cwiki.apache.org/confluence/display/Hive/StorageHandlers
After a lot of mistakes, in addition to above explanations, I would add simpler answers.
Case 1: Add new column named new_column
ALTER TABLE schema.table_name
ADD new_column INT COMMENT 'new number column');
Case 2: Rename a column new_column to no_of_days
ALTER TABLE schema.table_name
CHANGE new_column no_of_days INT;
Note that in renaming, both columns should be of same datatype like above as INT
For external table its simple and easy.
Just drop the table schema then edit create table schema , at last again create table with new schema.
example table: aparup_test.tbl_schema_change and will drop column id
steps:-
------------- show create table to fetch schema ------------------
spark.sql("""
show create table aparup_test.tbl_schema_change
""").show(100,False)
o/p:
CREATE EXTERNAL TABLE aparup_test.tbl_schema_change(name STRING, time_details TIMESTAMP, id BIGINT)
ROW FORMAT SERDE 'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe'
WITH SERDEPROPERTIES (
'serialization.format' = '1'
)
STORED AS
INPUTFORMAT 'org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat'
LOCATION 'gs://aparup_test/tbl_schema_change'
TBLPROPERTIES (
'parquet.compress' = 'snappy'
)
""")
------------- drop table --------------------------------
spark.sql("""
drop table aparup_test.tbl_schema_change
""").show(100,False)
------------- edit create table schema by dropping column "id"------------------
CREATE EXTERNAL TABLE aparup_test.tbl_schema_change(name STRING, time_details TIMESTAMP)
ROW FORMAT SERDE 'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe'
WITH SERDEPROPERTIES (
'serialization.format' = '1'
)
STORED AS
INPUTFORMAT 'org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat'
LOCATION 'gs://aparup_test/tbl_schema_change'
TBLPROPERTIES (
'parquet.compress' = 'snappy'
)
""")
------------- sync up table schema with parquet files ------------------
spark.sql("""
msck repair table aparup_test.tbl_schema_change
""").show(100,False)
==================== DONE =====================================
Even below query is working for me.
Alter table tbl_name drop col_name

Hive, Bucketing for the partitioned table

This is my script:
--table without partition
drop table if exists ufodata;
create table ufodata ( sighted string, reported string, city string, shape string, duration string, description string )
row format delimited
fields terminated by '\t'
Location '/mapreduce/hive/ufo';
--load my data in ufodata
load data local inpath '/home/training/downloads/ufo_awesome.tsv' into table ufodata;
--create partition table
drop table if exists partufo;
create table partufo ( sighted string, reported string, city string, shape string, duration string, description string )
partitioned by ( year string )
clustered by (year) into 6 buckets
row format delimited
fields terminated by '/t';
--by default dynamic partition is not set
set hive.exec.dynamic.partition=true;
set hive.exec.dynamic.partition.mode=nonstrict;
--by default bucketing is false
set hive.enforcebucketing=true;
--loading mydata
insert overwrite table partufo
partition (year)
select sighted, reported, city, shape, min, description, SUBSTR(TRIM(sighted), 1,4) from ufodata;
Error message:
FAILED: Error in semantic analysis: Invalid column reference
I tried bucketing for my partitioned table. If I remove "clustered by (year) into 6 buckets" the script works fine. How do I bucket the partitioned table
There is an important thing we should consider while doing bucketing in hive.
The same column name cannot be used for both bucketing and partitioning. The reason is as follows:
Clustering and Sorting happens within a partition. Inside each partition there will be only one value associated with the partition column(in your case it is year)therefore there will not any be any impact on clustering and sorting. That is the reason for your error....
You can use the below syntax to create bucketing table with partition.
CREATE TABLE bckt_movies
(mov_id BIGINT , mov_name STRING ,prod_studio STRING, col_world DOUBLE , col_us_canada DOUBLE , col_uk DOUBLE , col_aus DOUBLE)
PARTITIONED BY (rel_year STRING)
CLUSTERED BY(mov_id) INTO 6 BUCKETS;
when you're doing dynamic partition, create a temporary table with all the columns (including your partitioned column) and load data into temporary table.
create actual partitioned table with partition column. While you are loading data from temporary table the partitioned column should be in the last in the select clause.

hive external partitioned table

First i created hive external table partitioned by code and date
CREATE EXTERNAL TABLE IF NOT EXISTS XYZ
(
ID STRING,
SAL BIGINT,
NAME STRING,
)
PARTITIONED BY (CODE INT,DATE STRING)
ROW FORMAT SERDE 'parquet.hive.serde.ParquetHiveSerDe'
STORED AS
INPUTFORMAT "parquet.hive.DeprecatedParquetInputFormat"
OUTPUTFORMAT "parquet.hive.DeprecatedParquetOutputFormat"
LOCATION '/old_work/XYZ';
and then i execute insert overwrite on this table taking data from other table
INSERT OVERWRITE TABLE XYZ PARTITION (CODE,DATE)
SELECT
*
FROM TEMP_XYZ;
and after that i count the number of records in hive
select count(*) from XYZ;
it shows me 1000 records are there
and then i rename or move the location '/old_work/XYZ' to '/new_work/XYZ'
and then i again drop the XYZ table and created again pointing location to new directory
means '/new_work/XYZ'
CREATE EXTERNAL TABLE IF NOT EXISTS XYZ
(
ID STRING,
SAL BIGINT,
NAME STRING,
)
PARTITIONED BY (CODE INT,DATE STRING)
ROW FORMAT SERDE 'parquet.hive.serde.ParquetHiveSerDe'
STORED AS
INPUTFORMAT "parquet.hive.DeprecatedParquetInputFormat"
OUTPUTFORMAT "parquet.hive.DeprecatedParquetOutputFormat"
LOCATION '/new_work/XYZ';
But then when i execute select count(*) from XYZ table in hive , it shows 0 records ,
i think i missed something , please help me on this????
You need not drop the table and re create it the second time:
As soon as you move or rename a external hdfs location of the table just do this :
msck repair table <table_name>
In your case the error was because, The hive metastore wasnt updated with the new path .

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