List of Pages in Category Developers (275 pages)
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A
- ABORT_ON_ERROR Query Option
- Accessing Avro Data Files From Spark SQL Applications
- Accessing Data Stored in Amazon S3 through Spark
- Accessing Data Stored in Azure Data Lake Store (ADLS) through Spark
- Accessing External Storage from Spark
- Accessing HBase by using the HBase Shell
- Accessing HBase by using the HBase Shell
- Accessing Parquet Files From Spark SQL Applications
- Accessing Table Data with MapReduce
- Accessing Table Data with Pig
- ALTER DATABASE Statement
- ALTER TABLE Statement
- ALTER VIEW Statement
- Apache Hive Overview in CDH
- Apache Impala - Interactive SQL
- Apache Parquet Tables with Hive in CDH
- APPX_COUNT_DISTINCT Query Option (CDH 5.2 or higher only)
- APPX_MEDIAN Function
- ARRAY Complex Type (CDH 5.5 or higher only)
- AVG Function
)B
- Batch Indexing Using Cloudera Search
- BATCH_SIZE Query Option
- Benchmarking Impala Queries
- BIGINT Data Type
- BOOLEAN Data Type
- BUFFER_POOL_LIMIT Query Option
- Building and Running a Crunch Application with Spark
- Building Spark Applications
C
- CHAR Data Type (CDH 5.2 or higher only)
- Cloudera Search Overview
- COMMENT Statement
- Comments
- Complex Types (CDH 5.5 or higher only)
- Components of the Impala Server
- COMPRESSION_CODEC Query Option (CDH 5.2 or higher only)
- COMPUTE STATS Statement
- COMPUTE_STATS_MIN_SAMPLE_SIZE Query Option
- Configuration Settings for HBase
- Configuring Impala Delegation for Hue and BI Tools
- Configuring Impala to Work with JDBC
- Configuring Impala to Work with JDBC
- Configuring Impala to Work with ODBC
- Configuring Impala to Work with ODBC
- Configuring Quotas
- Connecting to impalad through impala-shell
- Controlling Impala Resource Usage
- COUNT Function
- CREATE DATABASE Statement
- CREATE FUNCTION Statement
- CREATE ROLE Statement (CDH 5.2 or higher only)
- CREATE TABLE Statement
- CREATE VIEW Statement
- Customizing Time Zones
D
- Data Types
- DDL Statements
- DEBUG_ACTION Query Option
- DECIMAL Data Type (CDH 6.0 / Impala 3.0 or higher only)
- DEFAULT_JOIN_DISTRIBUTION_MODE Query Option
- DEFAULT_SPILLABLE_BUFFER_SIZE Query Option
- DELETE Statement (CDH 5.10 or higher only)
- DESCRIBE Statement
- Detecting and Correcting HDFS Block Skew Conditions
- Developing and Running a Spark WordCount Application
- Developing Applications With Apache Kudu
- Developing Impala Applications
- Developing Kafka Clients
- Developing Spark Applications
- DISABLE_CODEGEN_ROWS_THRESHOLD Query Option (CDH 5.13 / Impala 2.10 or higher only)
- DISABLE_ROW_RUNTIME_FILTERING Query Option (CDH 5.7 or higher only)
- DISABLE_STREAMING_PREAGGREGATIONS Query Option (CDH 5.7 or higher only)
- DISABLE_UNSAFE_SPILLS Query Option (CDH 5.2 or higher only)
- DISTINCT Operator
- DML Statements
- DOUBLE Data Type
- DROP DATABASE Statement
- DROP FUNCTION Statement
- DROP ROLE Statement (CDH 5.2 or higher only)
- DROP STATS Statement
- DROP TABLE Statement
E
- EXEC_SINGLE_NODE_ROWS_THRESHOLD Query Option (CDH 5.3 or higher only)
- EXEC_TIME_LIMIT_S Query Option (CDH 5.15 / Impala 2.12 or higher only)
- EXPLAIN Statement
- EXPLAIN_LEVEL Query Option
F
G
- GRANT Statement (CDH 5.2 or higher only)
- GROUP BY Clause
- GROUP_CONCAT Function
- Guidelines for Designing Impala Schemas
H
- HAVING Clause
- HBase Filtering
- HBASE_CACHE_BLOCKS Query Option
- HBASE_CACHING Query Option
- How Impala Fits Into the Hadoop Ecosystem
- How Impala Works with Hadoop File Formats
I
- IDLE_SESSION_TIMEOUT Query Option (CDH 5.15 / Impala 2.12 or higher only)
- Impala
- Impala Aggregate Functions
- Impala Analytic Functions
- Impala Bit Functions
- Impala Built-In Functions
- Impala Concepts and Architecture
- Impala Conditional Functions
- Impala Date and Time Functions
- Impala Frequently Asked Questions
- Impala Mathematical Functions
- Impala Miscellaneous Functions
- Impala Performance Guidelines and Best Practices
- Impala Requirements
- Impala Requirements
- Impala Reserved Words
- Impala Schema Objects and Object Names
- Impala SQL Language Reference
- Impala SQL Statements
- Impala String Functions
- Impala Tutorials
- Impala Type Conversion Functions
- Impala Web User Interface for Debugging
- impala-shell Command Reference
- impala-shell Configuration Options
- Importing Data Into HBase
- Importing Data into Hive with Sqoop Through HiverServer2
- Indexing Data Using Cloudera Search
- INSERT Statement
- INT Data Type
- INVALIDATE METADATA Statement
J
K
L
- LIMIT Clause
- Literals
- LIVE_PROGRESS Query Option (CDH 5.5 or higher only)
- LIVE_SUMMARY Query Option (CDH 5.5 or higher only)
- LOAD DATA Statement
M
- Managing Disk Space for Impala Data
- MAP Complex Type (CDH 5.5 or higher only)
- MapReduce Indexing
- MapReduceIndexerTool
- MAX Function
- MAX_ERRORS Query Option
- MAX_MEM_ESTIMATE_FOR_ADMISSION Query Option
- MAX_NUM_RUNTIME_FILTERS Query Option (CDH 5.7 or higher only)
- MAX_ROW_SIZE Query Option
- MAX_SCAN_RANGE_LENGTH Query Option
- MEM_LIMIT Query Option
- Metadata Management
- MIN Function
- MIN_SPILLABLE_BUFFER_SIZE Query Option
- Modifying Impala Startup Options
- MT_DOP Query Option
N
- NDV Function
- Near Real Time Indexing Using Cloudera Search
- NUM_NODES Query Option
- NUM_SCANNER_THREADS Query Option
O
- OFFSET Clause
- Optimizer Hints in Impala
- OPTIMIZE_PARTITION_KEY_SCANS Query Option (CDH 5.7 or higher only)
- ORDER BY Clause
- Overview of Impala Aliases
- Overview of Impala Databases
- Overview of Impala Functions
- Overview of Impala Identifiers
- Overview of Impala Tables
- Overview of Impala Views
- Overview of Ingesting and Querying Data with Apache Hive in CDH
P
- PARQUET_ANNOTATE_STRINGS_UTF8 Query Option (CDH 5.8 or higher only)
- PARQUET_ARRAY_RESOLUTION Query Option (CDH 5.12 or higher only)
- PARQUET_DICTIONARY_FILTERING Query Option (CDH 5.12 or higher only)
- PARQUET_FALLBACK_SCHEMA_RESOLUTION Query Option (CDH 5.8 or higher only)
- PARQUET_FILE_SIZE Query Option
- PARQUET_READ_STATISTICS Query Option (CDH 5.12 or higher only)
- Partitioning for Impala Tables
- Performance Considerations for Join Queries
- Planning for Impala Deployment
- Porting SQL from Other Database Systems to Impala
- Ports Used by Impala
- Predicate Pushdown in Parquet
- PREFETCH_MODE Query Option (CDH 5.8 or higher only)
Q
- Query Options for the SET Statement
- Query Vectorization for Apache Hive in CDH
- QUERY_TIMEOUT_S Query Option (CDH 5.2 or higher only)
R
- Reading Data from HBase
- REAL Data Type
- REFRESH FUNCTIONS Statement
- REFRESH Statement
- REPLICA_PREFERENCE Query Option (CDH 5.9 or higher only)
- REQUEST_POOL Query Option
- Resource Management
- RESOURCE_TRACE_RATIO Query Option (CDH 6.2 / Impala 3.2 or higher only)
- REVOKE Statement (CDH 5.2 or higher only)
- Running Commands and SQL Statements in impala-shell
- Running Spark Applications
- Running Spark Python Applications
- Runtime Filtering for Impala Queries (CDH 5.7 or higher only)
- RUNTIME_BLOOM_FILTER_SIZE Query Option (CDH 5.7 or higher only)
- RUNTIME_FILTER_MAX_SIZE Query Option (CDH 5.8 or higher only)
- RUNTIME_FILTER_MIN_SIZE Query Option (CDH 5.8 or higher only)
- RUNTIME_FILTER_MODE Query Option (CDH 5.7 or higher only)
- RUNTIME_FILTER_WAIT_TIME_MS Query Option (CDH 5.7 or higher only)
S
- S3_SKIP_INSERT_STAGING Query Option (CDH 5.8 or higher only)
- Scalability Considerations for Impala
- SCAN_BYTES_LIMIT Query Option (CDH 6.1 or higher only)
- SCHEDULE_RANDOM_REPLICA Query Option (CDH 5.7 or higher only)
- SCRATCH_LIMIT Query Option
- Search Guide
- SELECT Statement
- SET Statement
- SHOW Statement
- SHUTDOWN Statement
- SMALLINT Data Type
- Snappy Compression
- Spark and Hadoop Integration
- Spark and IPython and Jupyter Notebooks
- Spark Indexing
- Specifying Impala Credentials to Access Data in S3
- Specifying Impala Credentials to Access Data in S3 with Cloudera Manager
- SQL Differences Between Impala and Hive
- SQL Operators
- STDDEV, STDDEV_SAMP, STDDEV_POP Functions
- STRING Data Type
- STRUCT Complex Type (CDH 5.5 or higher only)
- Subqueries in Impala SELECT Statements
- SUM Function
- Supported Sources, Sinks, and Channels
- SYNC_DDL Query Option
T
- Table and Column Statistics
- TABLESAMPLE Clause
- Testing Impala Performance
- THREAD_RESERVATION_AGGREGATE_LIMIT Query Option (CDH 6.1 or higher only)
- THREAD_RESERVATION_LIMIT Query Option (CDH 6.1 or higher only)
- TIMESTAMP Data Type
- TIMEZONE Query Option (CDH 6.1 / Impala 3.1 or higher only)
- TINYINT Data Type
- TOPN_BYTES_LIMIT Query Option (CDH 6.1 / Impala 3.1 or higher only)
- Troubleshooting for Spark
- Troubleshooting Impala
- TRUNCATE TABLE Statement (CDH 5.5 or higher only)
- Tuning Impala for Performance
U
- Understanding Impala Query Performance - EXPLAIN Plans and Query Profiles
- UNION Clause
- UPDATE Statement (CDH 5.10 or higher only)
- UPSERT Statement (CDH 5.10 or higher only)
- USE Statement
- User-Defined Functions (UDFs)
- Using & Managing Apache Hive in CDH
- Using Apache Avro Data Files with CDH
- Using Apache Hive with HBase in CDH
- Using Apache Parquet Data Files with CDH
- Using CDH with Isilon Storage
- Using HBase Command-Line Utilities
- Using HDFS Caching with Impala (CDH 5.3 or higher only)
- Using Impala Logging
- Using Impala through a Proxy for High Availability
- Using Impala to Query HBase Tables
- Using Impala to Query Kudu Tables
- Using Impala with the Amazon S3 Filesystem
- Using Impala with the Azure Data Lake Store (ADLS)
- Using MapReduce Batch Indexing to Index Sample Tweets
- Using MapReduce with HBase
- Using PySpark
- Using Spark MLlib
- Using Spark SQL
- Using Spark Streaming
- Using Text Data Files with Impala Tables
- Using the Avro File Format with Impala Tables
- Using the Cloudera Manager API for Cluster Automation
- Using the Impala Shell (impala-shell Command)
- Using the ORC File Format with Impala Tables
- Using the Parquet File Format with Impala Tables
- Using the RCFile File Format with Impala Tables
- Using the SequenceFile File Format with Impala Tables
V
- VALUES Statement
- VARCHAR Data Type (CDH 5.2 or higher only)
- VARIANCE, VARIANCE_SAMP, VARIANCE_POP, VAR_SAMP, VAR_POP Functions
W