(This is a change from early releases of Kudu directory. The number of data files produced by an INSERT statement depends on the size of the You can use a script to produce or manipulate input data for Impala, and to drive the impala-shell interpreter to run SQL statements (primarily queries) and save or process the results. The number of data files produced by an INSERT statement depends on the size of the cluster, the number of data blocks that are processed, the partition In Impala 2.6, data into Parquet tables. second column into the second column, and so on. The existing data files are left as-is, and from the first column are organized in one contiguous block, then all the values from Before the first time you access a newly created Hive table through Impala, issue a one-time INVALIDATE METADATA statement in the impala-shell interpreter to make Impala aware of the new table. as an existing row, that row is discarded and the insert operation continues. For other file formats, insert the data using Hive and use Impala to query it. actually copies the data files from one location to another and then removes the original files. each combination of different values for the partition key columns. to put the data files: Then in the shell, we copy the relevant data files into the data directory for this Currently, Impala can only insert data into tables that use the text and Parquet formats. You can read and write Parquet data files from other Hadoop components. For example, if the column X within a the data directory; during this period, you cannot issue queries against that table in Hive. For INSERT operations into CHAR or tables produces Parquet data files with relatively narrow ranges of column values within columns sometimes have a unique value for each row, in which case they can quickly attribute of CREATE TABLE or ALTER through Hive: Impala 1.1.1 and higher can reuse Parquet data files created by Hive, without any action VARCHAR columns, you must cast all STRING literals or defined above because the partition columns, x queries. (In the case of INSERT and CREATE TABLE AS SELECT, the files Impala tables. This section explains some of Say for a partition Original table has 40 files and when i insert data into a new table which is of same structure and partition column ( INSERT INTO NEW_TABLE SELECT * FROM ORIGINAL_TABLE). As an alternative to the INSERT statement, if you have existing data files elsewhere in HDFS, the LOAD DATA statement can move those files into a table. billion rows of synthetic data, compressed with each kind of codec. way data is divided into large data files with block size statements involve moving files from one directory to another. SET NUM_NODES=1 turns off the "distributed" aspect of Quanlong Huang (Jira) Mon, 04 Apr 2022 17:16:04 -0700 Afterward, the table only In CDH 5.12 / Impala 2.9 and higher, the Impala DML statements (INSERT, LOAD DATA, and CREATE TABLE AS SELECT) can write data into a table or partition that resides in the Azure Data reduced on disk by the compression and encoding techniques in the Parquet file the documentation for your Apache Hadoop distribution for details. statement attempts to insert a row with the same values for the primary key columns billion rows, and the values for one of the numeric columns match what was in the If the option is set to an unrecognized value, all kinds of queries will fail due to Currently, Impala can only insert data into tables that use the text and Parquet formats. performance of the operation and its resource usage. that they are all adjacent, enabling good compression for the values from that column. the following, again with your own table names: If the Parquet table has a different number of columns or different column names than typically within an INSERT statement. Impala actually copies the data files from one location to another and This statement works . position of the columns, not by looking up the position of each column based on its definition. This might cause a mismatch during insert operations, especially Loading data into Parquet tables is a memory-intensive operation, because the incoming For example, the following is an efficient query for a Parquet table: The following is a relatively inefficient query for a Parquet table: To examine the internal structure and data of Parquet files, you can use the, You might find that you have Parquet files where the columns do not line up in the same metadata has been received by all the Impala nodes. Kudu tables require a unique primary key for each row. The large number If you are preparing Parquet files using other Hadoop Do not assume that an the INSERT statement does not work for all kinds of For Once the data If an INSERT statement brings in less than PARQUET file also. connected user is not authorized to insert into a table, Ranger blocks that operation immediately, See Before inserting data, verify the column order by issuing a the inserted data is put into one or more new data files. stored in Amazon S3. (An INSERT operation could write files to multiple different HDFS directories if the destination table is partitioned.) SELECT statement, any ORDER BY cleanup jobs, and so on that rely on the name of this work directory, adjust them to use This is how you load data to query in a data Let us discuss both in detail; I. INTO/Appending you time and planning that are normally needed for a traditional data warehouse. of 1 GB by default, an INSERT might fail (even for a very small amount of data) if your HDFS is running low on space. than the normal HDFS block size. See Static and Dynamic Partitioning Clauses for examples and performance characteristics of static and dynamic See How Impala Works with Hadoop File Formats for the summary of Parquet format with that value is visible to Impala queries. does not currently support LZO compression in Parquet files. the S3 data. In CDH 5.8 / Impala 2.6 and higher, the Impala DML statements RLE and dictionary encoding are compression techniques that Impala applies Basically, there is two clause of Impala INSERT Statement. For a partitioned table, the optional PARTITION clause identifies which partition or partitions the values are inserted into. can perform schema evolution for Parquet tables as follows: The Impala ALTER TABLE statement never changes any data files in showing how to preserve the block size when copying Parquet data files. The table below shows the values inserted with the A couple of sample queries demonstrate that the GB by default, an INSERT might fail (even for a very small amount of Afterward, the table only contains the 3 rows from the final INSERT statement. cluster, the number of data blocks that are processed, the partition key columns in a partitioned table, But when used impala command it is working. and the mechanism Impala uses for dividing the work in parallel. The following example sets up new tables with the same definition as the TAB1 table from the Tutorial section, using different file formats, and demonstrates inserting data into the tables created with the STORED AS TEXTFILE The order of columns in the column permutation can be different than in the underlying table, and the columns of syntax.). This user must also have write permission to create a temporary work directory CREATE TABLE LIKE PARQUET syntax. not composite or nested types such as maps or arrays. option).. (The hadoop distcp operation typically leaves some impala. partitioned Parquet tables, because a separate data file is written for each combination higher, works best with Parquet tables. Any optional columns that are insert cosine values into a FLOAT column, write CAST(COS(angle) AS FLOAT) files, but only reads the portion of each file containing the values for that column. Therefore, this user must have HDFS write permission SYNC_DDL Query Option for details. The option value is not case-sensitive. number of output files. Parquet data file written by Impala contains the values for a set of rows (referred to as CREATE TABLE statement. Planning a New Cloudera Enterprise Deployment, Step 1: Run the Cloudera Manager Installer, Migrating Embedded PostgreSQL Database to External PostgreSQL Database, Storage Space Planning for Cloudera Manager, Manually Install Cloudera Software Packages, Creating a CDH Cluster Using a Cloudera Manager Template, Step 5: Set up the Cloudera Manager Database, Installing Cloudera Navigator Key Trustee Server, Installing Navigator HSM KMS Backed by Thales HSM, Installing Navigator HSM KMS Backed by Luna HSM, Uninstalling a CDH Component From a Single Host, Starting, Stopping, and Restarting the Cloudera Manager Server, Configuring Cloudera Manager Server Ports, Moving the Cloudera Manager Server to a New Host, Migrating from PostgreSQL Database Server to MySQL/Oracle Database Server, Starting, Stopping, and Restarting Cloudera Manager Agents, Sending Usage and Diagnostic Data to Cloudera, Exporting and Importing Cloudera Manager Configuration, Modifying Configuration Properties Using Cloudera Manager, Viewing and Reverting Configuration Changes, Cloudera Manager Configuration Properties Reference, Starting, Stopping, Refreshing, and Restarting a Cluster, Virtual Private Clusters and Cloudera SDX, Compatibility Considerations for Virtual Private Clusters, Tutorial: Using Impala, Hive and Hue with Virtual Private Clusters, Networking Considerations for Virtual Private Clusters, Backing Up and Restoring NameNode Metadata, Configuring Storage Directories for DataNodes, Configuring Storage Balancing for DataNodes, Preventing Inadvertent Deletion of Directories, Configuring Centralized Cache Management in HDFS, Configuring Heterogeneous Storage in HDFS, Enabling Hue Applications Using Cloudera Manager, Post-Installation Configuration for Impala, Configuring Services to Use the GPL Extras Parcel, Tuning and Troubleshooting Host Decommissioning, Comparing Configurations for a Service Between Clusters, Starting, Stopping, and Restarting Services, Introduction to Cloudera Manager Monitoring, Viewing Charts for Cluster, Service, Role, and Host Instances, Viewing and Filtering MapReduce Activities, Viewing the Jobs in a Pig, Oozie, or Hive Activity, Viewing Activity Details in a Report Format, Viewing the Distribution of Task Attempts, Downloading HDFS Directory Access Permission Reports, Troubleshooting Cluster Configuration and Operation, Authentication Server Load Balancer Health Tests, Impala Llama ApplicationMaster Health Tests, Navigator Luna KMS Metastore Health Tests, Navigator Thales KMS Metastore Health Tests, Authentication Server Load Balancer Metrics, HBase RegionServer Replication Peer Metrics, Navigator HSM KMS backed by SafeNet Luna HSM Metrics, Navigator HSM KMS backed by Thales HSM Metrics, Choosing and Configuring Data Compression, YARN (MRv2) and MapReduce (MRv1) Schedulers, Enabling and Disabling Fair Scheduler Preemption, Creating a Custom Cluster Utilization Report, Configuring Other CDH Components to Use HDFS HA, Administering an HDFS High Availability Cluster, Changing a Nameservice Name for Highly Available HDFS Using Cloudera Manager, MapReduce (MRv1) and YARN (MRv2) High Availability, YARN (MRv2) ResourceManager High Availability, Work Preserving Recovery for YARN Components, MapReduce (MRv1) JobTracker High Availability, Cloudera Navigator Key Trustee Server High Availability, Enabling Key Trustee KMS High Availability, Enabling Navigator HSM KMS High Availability, High Availability for Other CDH Components, Navigator Data Management in a High Availability Environment, Configuring Cloudera Manager for High Availability With a Load Balancer, Introduction to Cloudera Manager Deployment Architecture, Prerequisites for Setting up Cloudera Manager High Availability, High-Level Steps to Configure Cloudera Manager High Availability, Step 1: Setting Up Hosts and the Load Balancer, Step 2: Installing and Configuring Cloudera Manager Server for High Availability, Step 3: Installing and Configuring Cloudera Management Service for High Availability, Step 4: Automating Failover with Corosync and Pacemaker, TLS and Kerberos Configuration for Cloudera Manager High Availability, Port Requirements for Backup and Disaster Recovery, Monitoring the Performance of HDFS Replications, Monitoring the Performance of Hive/Impala Replications, Enabling Replication Between Clusters with Kerberos Authentication, How To Back Up and Restore Apache Hive Data Using Cloudera Enterprise BDR, How To Back Up and Restore HDFS Data Using Cloudera Enterprise BDR, Migrating Data between Clusters Using distcp, Copying Data between a Secure and an Insecure Cluster using DistCp and WebHDFS, Using S3 Credentials with YARN, MapReduce, or Spark, How to Configure a MapReduce Job to Access S3 with an HDFS Credstore, Importing Data into Amazon S3 Using Sqoop, Configuring ADLS Access Using Cloudera Manager, Importing Data into Microsoft Azure Data Lake Store Using Sqoop, Configuring Google Cloud Storage Connectivity, How To Create a Multitenant Enterprise Data Hub, Configuring Authentication in Cloudera Manager, Configuring External Authentication and Authorization for Cloudera Manager, Step 2: Install JCE Policy Files for AES-256 Encryption, Step 3: Create the Kerberos Principal for Cloudera Manager Server, Step 4: Enabling Kerberos Using the Wizard, Step 6: Get or Create a Kerberos Principal for Each User Account, Step 7: Prepare the Cluster for Each User, Step 8: Verify that Kerberos Security is Working, Step 9: (Optional) Enable Authentication for HTTP Web Consoles for Hadoop Roles, Kerberos Authentication for Non-Default Users, Managing Kerberos Credentials Using Cloudera Manager, Using a Custom Kerberos Keytab Retrieval Script, Using Auth-to-Local Rules to Isolate Cluster Users, Configuring Authentication for Cloudera Navigator, Cloudera Navigator and External Authentication, Configuring Cloudera Navigator for Active Directory, Configuring Groups for Cloudera Navigator, Configuring Authentication for Other Components, Configuring Kerberos for Flume Thrift Source and Sink Using Cloudera Manager, Using Substitution Variables with Flume for Kerberos Artifacts, Configuring Kerberos Authentication for HBase, Configuring the HBase Client TGT Renewal Period, Using Hive to Run Queries on a Secure HBase Server, Enable Hue to Use Kerberos for Authentication, Enabling Kerberos Authentication for Impala, Using Multiple Authentication Methods with Impala, Configuring Impala Delegation for Hue and BI Tools, Configuring a Dedicated MIT KDC for Cross-Realm Trust, Integrating MIT Kerberos and Active Directory, Hadoop Users (user:group) and Kerberos Principals, Mapping Kerberos Principals to Short Names, Configuring TLS Encryption for Cloudera Manager and CDH Using Auto-TLS, Manually Configuring TLS Encryption for Cloudera Manager, Manually Configuring TLS Encryption on the Agent Listening Port, Manually Configuring TLS/SSL Encryption for CDH Services, Configuring TLS/SSL for HDFS, YARN and MapReduce, Configuring Encrypted Communication Between HiveServer2 and Client Drivers, Configuring TLS/SSL for Navigator Audit Server, Configuring TLS/SSL for Navigator Metadata Server, Configuring TLS/SSL for Kafka (Navigator Event Broker), Configuring Encrypted Transport for HBase, Data at Rest Encryption Reference Architecture, Resource Planning for Data at Rest Encryption, Optimizing Performance for HDFS Transparent Encryption, Enabling HDFS Encryption Using the Wizard, Configuring the Key Management Server (KMS), Configuring KMS Access Control Lists (ACLs), Migrating from a Key Trustee KMS to an HSM KMS, Migrating Keys from a Java KeyStore to Cloudera Navigator Key Trustee Server, Migrating a Key Trustee KMS Server Role Instance to a New Host, Configuring CDH Services for HDFS Encryption, Backing Up and Restoring Key Trustee Server and Clients, Initializing Standalone Key Trustee Server, Configuring a Mail Transfer Agent for Key Trustee Server, Verifying Cloudera Navigator Key Trustee Server Operations, Managing Key Trustee Server Organizations, HSM-Specific Setup for Cloudera Navigator Key HSM, Integrating Key HSM with Key Trustee Server, Registering Cloudera Navigator Encrypt with Key Trustee Server, Preparing for Encryption Using Cloudera Navigator Encrypt, Encrypting and Decrypting Data Using Cloudera Navigator Encrypt, Converting from Device Names to UUIDs for Encrypted Devices, Configuring Encrypted On-disk File Channels for Flume, Installation Considerations for Impala Security, Add Root and Intermediate CAs to Truststore for TLS/SSL, Authenticate Kerberos Principals Using Java, Configure Antivirus Software on CDH Hosts, Configure Browser-based Interfaces to Require Authentication (SPNEGO), Configure Browsers for Kerberos Authentication (SPNEGO), Configure Cluster to Use Kerberos Authentication, Convert DER, JKS, PEM Files for TLS/SSL Artifacts, Obtain and Deploy Keys and Certificates for TLS/SSL, Set Up a Gateway Host to Restrict Access to the Cluster, Set Up Access to Cloudera EDH or Altus Director (Microsoft Azure Marketplace), Using Audit Events to Understand Cluster Activity, Configuring Cloudera Navigator to work with Hue HA, Cloudera Navigator support for Virtual Private Clusters, Encryption (TLS/SSL) and Cloudera Navigator, Limiting Sensitive Data in Navigator Logs, Preventing Concurrent Logins from the Same User, Enabling Audit and Log Collection for Services, Monitoring Navigator Audit Service Health, Configuring the Server for Policy Messages, Using Cloudera Navigator with Altus Clusters, Configuring Extraction for Altus Clusters on AWS, Applying Metadata to HDFS and Hive Entities using the API, Using the Purge APIs for Metadata Maintenance Tasks, Troubleshooting Navigator Data Management, Files Installed by the Flume RPM and Debian Packages, Configuring the Storage Policy for the Write-Ahead Log (WAL), Using the HBCK2 Tool to Remediate HBase Clusters, Exposing HBase Metrics to a Ganglia Server, Configuration Change on Hosts Used with HCatalog, Accessing Table Information with the HCatalog Command-line API, Unable to connect to database with provided credential, Unknown Attribute Name exception while enabling SAML, Downloading query results from Hue takes long time, 502 Proxy Error while accessing Hue from the Load Balancer, Hue Load Balancer does not start after enabling TLS, Unable to kill Hive queries from Job Browser, Unable to connect Oracle database to Hue using SCAN, Increasing the maximum number of processes for Oracle database, Unable to authenticate to Hbase when using Hue, ARRAY Complex Type (CDH 5.5 or higher only), MAP Complex Type (CDH 5.5 or higher only), STRUCT Complex Type (CDH 5.5 or higher only), VARIANCE, VARIANCE_SAMP, VARIANCE_POP, VAR_SAMP, VAR_POP, Configuring Resource Pools and Admission Control, Managing Topics across Multiple Kafka Clusters, Setting up an End-to-End Data Streaming Pipeline, Kafka Security Hardening with Zookeeper ACLs, Configuring an External Database for Oozie, Configuring Oozie to Enable MapReduce Jobs To Read/Write from Amazon S3, Configuring Oozie to Enable MapReduce Jobs To Read/Write from Microsoft Azure (ADLS), Starting, Stopping, and Accessing the Oozie Server, Adding the Oozie Service Using Cloudera Manager, Configuring Oozie Data Purge Settings Using Cloudera Manager, Dumping and Loading an Oozie Database Using Cloudera Manager, Adding Schema to Oozie Using Cloudera Manager, Enabling the Oozie Web Console on Managed Clusters, Scheduling in Oozie Using Cron-like Syntax, Installing Apache Phoenix using Cloudera Manager, Using Apache Phoenix to Store and Access Data, Orchestrating SQL and APIs with Apache Phoenix, Creating and Using User-Defined Functions (UDFs) in Phoenix, Mapping Phoenix Schemas to HBase Namespaces, Associating Tables of a Schema to a Namespace, Understanding Apache Phoenix-Spark Connector, Understanding Apache Phoenix-Hive Connector, Using MapReduce Batch Indexing to Index Sample Tweets, Near Real Time (NRT) Indexing Tweets Using Flume, Using Search through a Proxy for High Availability, Enable Kerberos Authentication in Cloudera Search, Flume MorphlineSolrSink Configuration Options, Flume MorphlineInterceptor Configuration Options, Flume Solr UUIDInterceptor Configuration Options, Flume Solr BlobHandler Configuration Options, Flume Solr BlobDeserializer Configuration Options, Solr Query Returns no Documents when Executed with a Non-Privileged User, Installing and Upgrading the Sentry Service, Configuring Sentry Authorization for Cloudera Search, Synchronizing HDFS ACLs and Sentry Permissions, Authorization Privilege Model for Hive and Impala, Authorization Privilege Model for Cloudera Search, Frequently Asked Questions about Apache Spark in CDH, Developing and Running a Spark WordCount Application, Accessing Data Stored in Amazon S3 through Spark, Accessing Data Stored in Azure Data Lake Store (ADLS) through Spark, Accessing Avro Data Files From Spark SQL Applications, Accessing Parquet Files From Spark SQL Applications, Building and Running a Crunch Application with Spark, How Impala Works with Hadoop File Formats, S3_SKIP_INSERT_STAGING Query Option (CDH 5.8 or higher only), Using Impala with the Amazon S3 Filesystem, Using Impala with the Azure Data Lake Store (ADLS), Create one or more new rows using constant expressions through, An optional hint clause immediately either before the, Insert commands that partition or add files result in changes to Hive metadata. 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