Facing issue on creating hive table on top of parquet file. Can someone help me on the same.? I have read many articles and followed the guidelines but not able to load a parquet file in Hive Table.
According "Using Parquet Tables in Hive" it is often useful to create the table as an external table pointing to the location where the files will be created, if a table will be populated with data files generated outside of Hive.
hive> create external table parquet_table_name (<yourParquetDataStructure>)
STORED AS PARQUET
LOCATION '/<yourPath>/<yourParquetFile>';
Related
Could you help me to load a couple of parquet files to Snowflake.
I've got about 250 parquet-files which stored in AWS stage.
250 files = 250 different tables.
I'd like to dynamically load them into Snowflake tables.
So, I need:
Get schema from parquet file... I've read that I could get the schema from parquet file using parquet-tools (Apache).
Create table using schema from the parquet file
Load data from parquet-file to this table.
Could anyone help me how to do that? Does exist the most efficient way to realize it? (by using GUI Snowflake, for example). Can't find it.
Thanks.
If the schema of the files is same you can put them in a single stage and use the Infer-Schema function. This will give you the schema of the parquet files.
https://docs.snowflake.com/en/sql-reference/functions/infer_schema.html
In case all files have different schema then I'm afraid you have to infer the schema on each file.
I have an hdfs folder with many csv.gz within, all with the same schema. My customer needs to read the content of these tables through Hive.
I tried to apply https://cwiki.apache.org/confluence/display/Hive/CompressedStorage . However it moves the file, whereas I need it to stay in its initial directory.
Another problem is that I should load each file one by one, I would rather create a table from the directory and not manage file individually.
I do not master Hive at all. Is his possible?
Yes, this is possible via Hive. You can create an external table and reference the existing HDFS location containing the gzip files. The schema for the data should be specified during the table creation.
hive> CREATE EXTERNAL TABLE my_data
(
column_1 int,
column_2 string
)
LOCATION 'hdfs:///my_data_folder_with_gzip_files';
I am now preparing to store data in .csv files into hive. Of course, because of the good performance of parquet file format, the hive table should is parquet format. So, the normal way, is to create a temp table whose format is textfile, then I load local CSV file data into this temp table, and finally, create a same-structure parquet table and use sql insert into parquet_table values (select * from textfile_table);.
But I don't think this temp textfile table is necessary. So, my question is, is there a way for me to load these local .csv files into hive parquet-format table directly, namely, not to resort the a temp table? Or a easier way to accomplish this task?
As stated in Hive documentation:
NO verification of data against the schema is performed by the load command.
If the file is in hdfs, it is moved into the Hive-controlled file system namespace.
You could skip a step by using CREATE TABLE AS SELECT for the parquet table.
So you'll have 3 steps:
Create text table defining the schema
Load data into text table (move the file into the new table)
CREATE TABLE parquet_table AS SELECT * FROM textfile_table STORED AS PARQUET; supported from hive 0.13
I have 1 TB data in my HDFS in .csv format. When I load it in my Hive table what will be the total size of data. I mean will there be 2 copies of same data i.e 1 Copy in HDFS and other in Hive table ? Plz clarify. Thanks in advance.
If you create a hive external table, you provide a HDFS location for the table and you store that data into that particular location.
When you create a hive internal table hive create a directory into /apps/hive/warehouse/ directory.
Say, your table name is table1 then your directory will be /apps/hive/warehouse/table1
This directory is also a HDFS directory and when you load data into the table into internal table it goes into its directory.
Hive creates a mapping between table and their corresponding HDFS location and hence when you read the data its reading from the corresponding mapped directory.
Hence there wont be duplicate copy of data corresponding to table and their HDFS location.
But if in your Hadoop cluster Data Replication factor is set to 3(default replication) then it will take 3TB cluster disk space(as you have 1TB data) but there wont be any effect of your hive table data.
Please see below link to know more about Data replication.
http://hadoop.apache.org/docs/r1.2.1/hdfs_design.html#Data+Replication
It depends whether you are creating an internal or external table in Hive.
If you create an external table in Hive, it will create a mapping on where your data is stored in HDFS and there won't be any duplication at all. Hive will automatically pick the data where ever it is stored in HDFS.
Read more about external tables here: https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DDL#LanguageManualDDL-ExternalTables
I am new to Hadoop and I just started working on Hive, I my understanding it provides a query language to process data in HDFS. With HiveQl we can create tables and load data into it from HDFS.
So my question is: where are those tables stored? Specifically if we have 100 GB file in our HDFS and we want to make a hive table out of that data what will be the size of that table and where is it stored?
If my understanding about this concept is wrong please correct me ..
If the table is 100GB you should consider an Hive External Table (as opposed to a "managed table", for the difference, see this).
With an external table the data itself will be still stored on the HDFS in the file path that you specify (note that you may specify a directory of files as long as they all have the same structure), but Hive will create a map of it in the meta-store whereas the managed table will store the data "in Hive".
When you drop a managed table, it drops the underlying data as opposed to dropping a hive external table which only drops the meta-data from the meta-store referencing that data.
Either way you are using only 100GB as viewed by the user and are taking advantage of the HDFS' robustness though duplication of the data.
Hive will create a directory on HDFS. If you didn't specify any location it will create a directory at /user/hive/warehouse on HDFS. After load command the files are moved to the /warehouse/tablename. You can also point to the HDFS directory if it contains partitions (if the files are partitioned), or use external table concept.