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-- This is a Hive program. Hive is an SQL-like language that compiles | |
-- into Hadoop Map/Reduce jobs. It's very popular among analysts at | |
-- Facebook, because it allows them to query enormous Hadoop data | |
-- stores using a language much like SQL. | |
-- Our logs are stored on the Hadoop Distributed File System, in the | |
-- directory /logs/randomhacks.net/access. They're ordinary Apache | |
-- logs in *.gz format. | |
-- | |
-- We want to pretend that these gzipped log files are a database table, | |
-- and use a regular expression to split lines into database columns. | |
CREATE EXTERNAL TABLE access( | |
host STRING, | |
identity STRING, | |
user STRING, | |
time STRING, | |
request STRING, | |
status STRING, | |
size STRING, | |
referer STRING, | |
agent STRING) | |
ROW FORMAT SERDE 'org.apache.hadoop.hive.contrib.serde2.RegexSerDe' | |
WITH SERDEPROPERTIES ( | |
"input.regex" = "([^ ]*) ([^ ]*) ([^ ]*) (-|\\[[^\\]]*\\]) ([^ \"]*|\"[^\"]*\") (-|[0-9]*) (-|[0-9]*)(?: ([^ \"]*|\"[^\"]*\") ([^ \"]*|\"[^\"]*\"))?", | |
"output.format.string" = "%1$s %2$s %3$s %4$s %5$s %6$s %7$s %8$s %9$s" | |
) | |
STORED AS TEXTFILE | |
LOCATION '/logs/randomhacks.net/access'; | |
-- We want to store our logs in HBase, which is designed to hold tables | |
-- with billions of rows and millions of columns. HBase stores rows | |
-- sorted by primary key, so you can efficiently read all records within | |
-- a given range of keys. | |
-- | |
-- Here, our key is a Unix time stamp, and we assume that it always has | |
-- the same number of digits (hey, this was a dodgy late night hack). | |
-- So we could easily grab all the records from a specific time period. | |
-- | |
-- We store our data in 3 column families: "m" for metadata, "r" for | |
-- referrer data, and "a" for user-agent data. This allows us to only | |
-- load a subset of columns for a given query. | |
CREATE EXTERNAL TABLE access_hbase( | |
key STRING, -- Unix time + ":" + unique identifier. | |
host STRING, -- The IP address of the host making the request. | |
identity STRING, -- ??? (raw log data) | |
user STRING, -- ??? (raw log data) | |
time BIGINT, -- Unix time, UTC. | |
method STRING, -- "GET", etc. | |
path STRING, -- "/logo.png", etc. | |
protocol STRING, -- "HTTP/1.1", etc. | |
status SMALLINT, -- 200, 404, etc. | |
size BIGINT, -- Response size, in bytes. | |
referer_host STRING, -- "www.google.com", etc. | |
referer STRING, -- Full referrer string. | |
agent STRING) -- Full agent string. | |
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler' | |
WITH SERDEPROPERTIES ( | |
"hbase.columns.mapping" = ":key,m:host,m:identity,m:user,m:time,m:method,m:path,m:protocol,m:status,m:size,r:referer_host,r:referer,a:agent" | |
) | |
TBLPROPERTIES ("hbase.table.name" = "randomhacks_access"); | |
-- Copy our data from raw Apache log files to HBase, cleaning it up as we go. This is basically | |
-- a pseudo-SQL query which calls a few Java helpers. | |
-- | |
-- Note the "TABLESAMPLE" clause, which says to pick one of every 20 records at random. | |
INSERT OVERWRITE TABLE access_hbase | |
SELECT concat(cast(unix_timestamp(time, "[dd/MMM/yyyy:HH:mm:ss Z]") AS STRING), ":", guid()) AS key, | |
host, | |
unquote_apache(identity), | |
unquote_apache(user), | |
unix_timestamp(time, "[dd/MMM/yyyy:HH:mm:ss Z]"), | |
re_extract(unquote_apache(request), "([^ ]*) ([^ ]*) ([^\"]*)", 1) AS method, | |
re_extract(unquote_apache(request), "([^ ]*) ([^ ]*) ([^\"]*)", 2) AS path, | |
re_extract(unquote_apache(request), "([^ ]*) ([^ ]*) ([^\"]*)", 3) AS protocol, | |
cast(status AS SMALLINT) AS status, | |
cast(size AS BIGINT) AS size, | |
re_extract(unquote_apache(referer), "[^:]+:?/+([^/]*).*", 1) AS referer_host, | |
unquote_apache(referer) AS referer, | |
unquote_apache(agent) | |
FROM access TABLESAMPLE(BUCKET 1 OUT OF 20 ON rand()) | |
WHERE unix_timestamp(time, "[dd/MMM/yyyy:HH:mm:ss Z]") IS NOT NULL; | |
-- Find the 50 most popular pages on the site. | |
SELECT path, count(*) AS cnt | |
FROM access_hbase GROUP BY path | |
ORDER BY cnt DESC LIMIT 50; | |
-- Categorize our articles by year and count how many hits each year received. | |
SELECT pubyear, count(*) | |
FROM (SELECT re_extract(path, "/articles/([0-9]+)/.*", 1) AS pubyear | |
FROM access_hbase) access | |
WHERE pubyear IS NOT NULL | |
GROUP BY pubyear; |
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