PXF is an extensible framework that allows a distributed database like Greenplum and Apache Cloudberry to query external data files, whose metadata is not managed by the database. PXF includes built-in connectors for accessing data that exists inside HDFS files, Hive tables, HBase tables, JDBC-accessible databases and more. Users can also create their own connectors to other data storage or processing engines.
This project is forked from greenplum/pxf and customized for Apache Cloudberry.
external-table/: Contains the Cloudberry extension implementing an External Table protocol handlerfdw/: Contains the Cloudberry extension implementing a Foreign Data Wrapper (FDW) for PXFserver/: Contains the server side code of PXF along with the PXF Service and all the Pluginscli/: Contains command line interface code for PXFautomation/: Contains the automation and integration tests for PXF against the various datasourcesci/: Contains CI/CD environment and scripts (including singlecluster Hadoop environment)regression/: Contains the end-to-end (integration) tests for PXF against the various datasources, utilizing the PostgreSQL testing frameworkpg_regressdownloads/: An empty directory that serves as a staging location for Cloudberry RPMs for the development Docker image
Below are the steps to build and install PXF along with its dependencies including Cloudberry and Hadoop.
Note
To start, ensure you have a ~/workspace directory and have cloned the pxf and its prerequisites (shown below) under it.
(The name workspace is not strictly required but will be used throughout this guide.)
mkdir -p ~/workspace
cd ~/workspace
git clone https://github.com/apache/cloudberry-pxf.gitTo build PXF, you must have:
-
GCC compiler,
makesystem,unzippackage,mavenfor running integration tests -
Installed Cloudberry
Either download and install Cloudberry RPM or build Cloudberry from the source by following instructions in the Cloudberry.
Assuming you have installed Cloudberry into
/usr/local/cloudberrydbdirectory, run its environment script:source /usr/local/cloudberrydb/greenplum_path.sh -
JDK 1.8 or JDK 11 to compile/run
Export your
JAVA_HOME:export JAVA_HOME=<PATH_TO_YOUR_JAVA_HOME> -
Go (1.9 or later)
To install Go on CentOS,
sudo yum install go. For other platforms, see the Go downloads page.Make sure to export your
GOPATHand add go to yourPATH. For example:export GOPATH=$HOME/go export PATH=$PATH:/usr/local/go/bin:$GOPATH/bin
Once you have installed Go, you will need the
ginkgotool which runs Go tests, respectively. Assuminggois on yourPATH, you can run:go install github.com/onsi/ginkgo/ginkgo@latest -
cURL (7.29 or later):
To install cURL devel package on CentOS 7,
sudo yum install libcurl-devel.Note that CentOS 6 provides an older, unsupported version of cURL (7.19). You should install a newer version from source if you are on CentOS 6.
PXF uses Makefiles to build its components. PXF server component uses Gradle that is wrapped into the Makefile for convenience.
cd ~/workspace/pxf
# Compile & Test PXF
make
# Only run unit tests
make testTo install PXF, first make sure that the user has sufficient permissions in the $GPHOME and $PXF_HOME directories to perform the installation. It's recommended to change ownership to match the installing user. For example, when installing PXF as user gpadmin under /usr/local/cloudberrydb:
export GPHOME=/usr/local/cloudberrydb
export PXF_HOME=/usr/local/pxf
export PXF_BASE=${HOME}/pxf-base
chown -R gpadmin:gpadmin "${GPHOME}" "${PXF_HOME}"
make -C ~/workspace/pxf installNOTE: if PXF_BASE is not set, it will default to PXF_HOME, and server configurations, libraries or other configurations, might get deleted after a PXF re-install.
Ensure that PXF is in your path. This command can be added to your .bashrc
export PATH=/usr/local/pxf/bin:$PATHThen you can prepare and start up PXF by doing the following.
pxf prepare
pxf startIf ${HOME}/pxf-base does not exist, pxf prepare will create the directory for you. This command should only need to be run once.
Note: Local development with PXF requires a running Cloudberry cluster.
Once the desired changes have been made, there are 2 options to re-install PXF:
- Run
make -sj4 installto re-install and run tests - Run
make -sj4 install-serverto only re-install the PXF server without running unit tests.
After PXF has been re-installed, you can restart the PXF instance using:
pxf restartIn order to demonstrate end to end functionality you will need Hadoop installed. We have all the related hadoop components (hdfs, hive, hbase, zookeeper, etc) mapped into simple artifact named singlecluster.
You can download from here and untar the singlecluster-HDP.tar.gz file, which contains everything needed to run Hadoop.
mv singlecluster-HDP.tar.gz ~/workspace/
cd ~/workspace
tar xzf singlecluster-HDP.tar.gzCreate a symlink using ln -s ~/workspace/singlecluster-HDP ~/workspace/singlecluster and then follow the steps in Setup Hadoop.
While PXF can run on either Java 8 or Java 11, please ensure that you are running Java 8 for hdfs, hadoop, etc. Please set your java version by seting your JAVA_HOME to the appropriate location.
On a Mac, you can set your java version using JAVA_HOME like so:
export JAVA_HOME=`/usr/libexec/java_home -v 1.8`
Initialize the default server configurations:
cp ${PXF_HOME}/templates/*-site.xml ${PXF_BASE}/servers/default
Note
Since the docker container will house all Single cluster Hadoop, Cloudberry and PXF, we recommend that you have at least 4 cpus and 6GB memory allocated to Docker. These settings are available under docker preferences.
The quick and easy is to download the Cloudberry RPM from GitHub and move it into the /downloads folder. Then run ./dev/start.bash to get a docker image with a running Cloudberry, Hadoop cluster and an installed PXF.
Configure, build and install Cloudberry. This will be needed only when you use the container for the first time with Cloudberry source.
~/workspace/pxf/dev/build_gpdb.bash
sudo mkdir /usr/local/cloudberry-db-devel
sudo chown gpadmin:gpadmin /usr/local/cloudberry-db-devel
~/workspace/pxf/dev/install_gpdb.bashFor subsequent minor changes to Cloudberry source you can simply do the following:
~/workspace/pxf/dev/install_gpdb.bashRun all the instructions below and run GROUP=smoke (in one script):
~/workspace/pxf/dev/smoke_shortcut.shCreate Cloudberry Cluster
source /usr/local/cloudberrydb-db-devel/greenplum_path.sh
make -C ~/workspace/cbdb create-demo-cluster
source ~/workspace/cbdb/gpAux/gpdemo/gpdemo-env.shHdfs will be needed to demonstrate functionality. You can choose to start additional hadoop components (hive/hbase) if you need them.
Setup User Impersonation prior to starting the hadoop components (this allows the gpadmin user to access hadoop data).
~/workspace/pxf/dev/configure_singlecluster.bashSetup and start HDFS
pushd ~/workspace/singlecluster/bin
echo y | ./init-gphd.sh
./start-hdfs.sh
popdStart other optional components based on your need
pushd ~/workspace/singlecluster/bin
# Start Hive
./start-yarn.sh
./start-hive.sh
# Start HBase
./start-zookeeper.sh
./start-hbase.sh
popdMinio is an S3-API compatible local storage solution. The development docker image comes with Minio software pre-installed. To start the Minio server, run the following script:
source ~/workspace/pxf/dev/start_minio.bashAfter the server starts, you can access Minio UI at http://localhost:9000 from the host OS. Use admin for the access key and password for the secret key when connecting to your local Minio instance.
The script also sets PROTOCOL=minio so that the automation framework will use the local Minio server when running S3 automation tests. If later you would like to run Hadoop HDFS tests, unset this variable with unset PROTOCOL command.
Install PXF Server
# Install PXF
make -C ~/workspace/pxf install
# Start PXF
export PXF_JVM_OPTS="-Xmx512m -Xms256m"
$PXF_HOME/bin/pxf startInstall PXF client (ignore if this is already done)
psql -d template1 -c "create extension pxf"All tests use a database named pxfautomation.
pushd ~/workspace/pxf/automation
# Initialize default server configs using template
cp ${PXF_HOME}/templates/{hdfs,mapred,yarn,core,hbase,hive}-site.xml ${PXF_BASE}/servers/default
# Run specific tests. Example: Hdfs Smoke Test
make TEST=HdfsSmokeTest
# Run all tests. This will be very time consuming.
make GROUP=gpdb
# If you wish to run test(s) against a different storage protocol set the following variable (for eg: s3)
export PROTOCOL=s3
popdIf you see any HBase failures, try copying pxf-hbase-*.jar to the HBase classpath, and restart HBase:
cp ${PXF_HOME}/lib/pxf-hbase-*.jar ~/workspace/singlecluster/hbase/lib/pxf-hbase.jar
~/workspace/singlecluster/bin/stop-hbase.sh
~/workspace/singlecluster/bin/start-hbase.sh
To deploy your changes to PXF in the development environment.
# $PXF_HOME folder is replaced each time you make install.
# So, if you have any config changes, you may want to back those up.
$PXF_HOME/bin/pxf stop
make -C ~/workspace/pxf install
# Make any config changes you had backed up previously
rm -rf $PXF_HOME/pxf-service
yes | $PXF_HOME/bin/pxf init
$PXF_HOME/bin/pxf start- Start IntelliJ. Click "Open" and select the directory to which you cloned the
pxfrepo. - Select
File > Project Structure. - Make sure you have a JDK (version 1.8) selected.
- In the
Project Settings > Modulessection, selectImport Module, pick thepxf/serverdirectory and import as a Gradle module. You may see an error saying that there's no JDK set for Gradle. Just cancel and retry. It goes away the second time. - Import a second module, giving the
pxf/automationdirectory, select "Import module from external model", pickMaventhen click Finish. - Restart IntelliJ
- Check that it worked by running a unit test (cannot currently run automation tests from IntelliJ) and making sure that imports, variables, and auto-completion function in the two modules.
- Optionally you can replace
${PXF_TMP_DIR}with${GPHOME}/pxf/tmpinautomation/pom.xml - Select
Tools > Create Command-line Launcher...to enable starting Intellij with theideacommand, e.g.cd ~/workspace/pxf && idea ..
- In IntelliJ, click
Edit Configurationand add a new one of typeRemote - Change the name to
PXF Service Boot - Change the port number to
2020 - Save the configuration
- Restart PXF in DEBUG Mode
PXF_DEBUG=true pxf restart - Debug the new configuration in IntelliJ
- Run a query in CloudberryDB that uses PXF to debug with IntelliJ
- Download bin_gpdb (from any of the pipelines)
- Download pxf_tarball (from any of the pipelines)
These instructions allow you to run a Kerberized cluster
docker run --rm -it \
--privileged \
--hostname c6401.ambari.apache.org \
-p 5432:5432 \
-p 5888:5888 \
-p 8000:8000 \
-p 8080:8080 \
-p 8020:8020 \
-p 9000:9000 \
-p 9090:9090 \
-p 50070:50070 \
-w /home/gpadmin/workspace \
-v ~/workspace/cbdb:/home/gpadmin/workspace/gpdb_src \
-v ~/workspace/pxf:/home/gpadmin/workspace/pxf_src \
-v ~/workspace/singlecluster-HDP:/home/gpadmin/workspace/singlecluster \
-v ~/Downloads/bin_cbdb:/home/gpadmin/workspace/bin_cbdb \
-v ~/Downloads/pxf_tarball:/home/gpadmin/workspace/pxf_tarball \
-e CLUSTER_NAME=hdp \
-e NODE=c6401.ambari.apache.org \
-e REALM=AMBARI.APACHE.ORG \
gcr.io/$PROJECT_ID/gpdb-pxf-dev/gpdb6-centos7-test-pxf-hdp2 /bin/bash
# Inside the container, you can use the scripts in ci/docker/pxf-cbdb-dev/ubuntu/script to set up and run tests.
echo "+----------------------------------------------+"
echo "| Kerberos admin principal: admin/admin@$REALM |"
echo "| Kerberos admin password : admin |"
echo "+----------------------------------------------+"
su - gpadminSee the CONTRIBUTING file for how to make contributions dedicated to the PXF for Cloudberry Database.
Under Apache License V2.0, See the LICENSE for details.