How do I write the contents of a deltalake table to a csv file in Azure databricks?
Is there a way where I do not have to first dump the contents to a dataframe? https://docs.databricks.com/delta/delta-batch.html
While loading the data to the Delta table, I used an ADLS Gen2 folder location for the creation of the versioned parquet files.
The conversion of parquet to CSV could then be accomplished using the Copy Data Activity in ADF.
You can simply use Insert Overwrite Directory.
The syntax would be
INSERT OVERWRITE DIRECTORY <directory_path> USING <file_format> <options> select * from table_name
Here you can specify the target directory path where to generate the file. The file could be parquet, csv, txt, json, etc.
Related
I would like to write an entire table to s3a in parquet format.
Let's call the table abc_schem.thattable. I would like to use an Impala query to
SELECT * WHERE to_date(create_time) = 'YYYY-MM-DD'
What is the exact syntax for this to write to Parquet S3?
You can create an external table in a specific location and insert into it assuming s3 system is already configured
CREATE EXTERNAL TABLE abc_schem.thattable(
...
)
STORED AS PARQUET
LOCATION 's3a://bucket/path';
Then use some LOAD DATA or INSERT INTO... SELECT... FROM commands to get data there
CREATE TABLE schema.temp_c
STORED AS PARQUET LOCATION "s3a://s3highlevel/c/lowlevel" AS
SELECT * FROM schema.table
i have a parquet file stored in hdfs called small in path:
/user/s/file.parquet
and want to create a table in hive containing it's content.
the schema of the file is very complected and i want hive to automatically import the schema from the file.
i want to do something like this:
CREATE EXTERNAL TABLE tableName
STORED AS PARQUET
LOCATION 'file/path'
is this possible?
thank you for your help.
Unfortunately it's not possible to create external table on a single file in Hive, just for directories. If /user/s/file.parquet is the only file in the directory you can indicate location as /user/s/ and Hive will catch up your file.
I have bunch of csv files listed inside zipped file in hdfs. Is there any way to create a hive table above those with right data?
Note: data is quoted with " in csv file.
I have a csv file called test.csv in hdfs. The file was placed there through filezilla. I am able to view the path as well as the contents of the file when I log in to Edge node through putty using the same account credentials that I used to place the file into hdfs. I then connect to Hive and try to create an external table specifying the location of my csv file in hdfs using the statement below:
CREATE EXTERNAL TABLE(col1 string, col2 string) ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' STORED AS ORC LOCATION '/file path'
when I execute this command it is creating an external table on hive but the table that is being created is empty with only the columns showing up which i have already mentioned in the create statement. My question is, am I specifying the correct path in the location parameter in the create statement above? I tried using the path which I see on filezilla when I placed my csv file into hdfs which is in the format home/servername/username/directory/subdirectory/file
but this returns an error saying the user whose username is specified in the path above does not have ALL privileges on the file path.
NOTE: I checked the permissions on the file and the directory in which it resides and the user has all permissions(read,write and execute).
I then tried changing the path into the format user/username/directory/subdirectory/file and when I did this I was able to create the external table however the table is empty and does not load all the data in the csv file on which it was created.
I also tried the alternative method of creating an internal table as below and then using the LOAD DATA INPATH command. But this also failed as I am getting an error saying that "there are no files existing at the specified path".
CREATE TABLE foobar(key string, stats map<string, bigint>)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
COLLECTION ITEMS TERMINATED BY '|'
MAP KEYS TERMINATED BY ':' ;
LOAD DATA INPATH '/tmp/foobar.csv' INTO TABLE foobar;
First thing you can't load csv file directly into Hive table which is specified with orc file format while creating. Orc is a compression technique to store data in optimised way. So you can load your data into orc format table by following below steps.
You should create a temp table as text file format.
Load data into it by using the command.
hive> load data in path.....
or else u can use location parameter while creating the table itself.
Now create a hive table as your required file format (RC, ORC, parquet, etc).
-Now load data into it by using following command.
hive> insert overwrite into table foobar as select * from temptbl;
You will get table in orc file format.
In second issue is if you Load data into the table by using LOAD DATA command, the data which is in your file will become empty and new dir will be created in default location (/user/hive/warehouse/) with the table name and data will moved into that file. So check in that location you will see the data.
I'm trying to read a large gzip file into hive through spark runtime
to convert into SequenceFile format
And, I want to do this efficiently.
As far as I know, Spark supports only one mapper per gzip file same as it does for text files.
Is there a way to change the number of mappers for a gzip file being read? or should I choose another format like parquet?
I'm stuck currently.
The problem is that my log file is json-like data save into txt-format and then was gzip - ed, so for reading I used org.apache.spark.sql.json.
The examples I have seen that show - converting data into SequenceFile have some simple delimiters as csv-format.
I used to execute this query:
create TABLE table_1
USING org.apache.spark.sql.json
OPTIONS (path 'dir_to/file_name.txt.gz');
But now I have to rewrite it in something like that:
CREATE TABLE table_1(
ID BIGINT,
NAME STRING
)
COMMENT 'This is table_1 stored as sequencefile'
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
STORED AS SEQUENCEFILE;
LOAD DATA INPATH 'dir_to/file_name.txt.gz' OVERWRITE INTO TABLE table_1;
LOAD DATA INPATH 'dir_to/file_name.txt.gz' INTO TABLE table_1;
INSERT OVERWRITE TABLE table_1 SELECT id, name from table_1_text;
INSERT INTO TABLE table_1 SELECT id, name from table_1_text;
Is this the optimal way of doing this, or is there a simpler approach to this problem?
Please help!
As gzip textfile file is not splitable ,only one mapper will be launched or
you have to choose other data formats if you want to use more than one
mappers.
If there are huge json files and you want to save storage on hdfs use bzip2
compression to compress your json files on hdfs.You can query .bzip2 json
files from hive without modifying anything.