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package sandcrawler
import java.util.Properties
import scala.util.parsing.json.JSONObject
import scala.util.Try
import cascading.property.AppProps
import cascading.tap.SinkMode
import cascading.tuple.Fields
import cascading.pipe.joiner._
import com.twitter.scalding._
import com.twitter.scalding.typed.TDsl._
import parallelai.spyglass.base.JobBase
import parallelai.spyglass.hbase.HBaseConstants.SourceMode
import parallelai.spyglass.hbase.HBasePipeConversions
import parallelai.spyglass.hbase.HBaseSource
// Type that represents a raw parsed CDX line
case class CdxLine(surt: String,
datetime: String,
url: String,
mime: String,
http_status: String,
sha1: String,
c_size: String,
offset: String,
warc: String)
/**
* CDX backfill:
* 1. parse CDX (all columns)
* 2. filter CDX (pdf, HTTP 200, etc)
* 3. source HBase (key column only)
* 4. left join CDX to HBase
* 5. filter to only those with null HBase key column
* 6. convert CDX fields to HBase columns
* 7. sink results to HBase
*
* TODO: I really mixed the Scalding "field-base" and "type-based" APIs here.
* Should decide on a best practice.
*/
class CdxBackfillJob(args: Args) extends JobBase(args) with HBasePipeConversions {
import CdxBackfillJob._
val hbaseSource = getHBaseSource(args("hbase-table"), args("zookeeper-hosts"))
val hbaseSink = getHBaseSink(args("hbase-table"), args("zookeeper-hosts"))
// Parse CDX lines from text file to typed pipe
val lines : TypedPipe[String] = TypedPipe.from(TextLine(args("cdx-input-path")))
val cdxLines : TypedPipe[CdxLine] = lines
.filter { isCdxLine }
.map { lineToCdxLine }
.filter { CdxBackfillJob.keepCdx(_) }
val cdxRows : TypedPipe[(String, String, String, String)] = cdxLines
.map { CdxBackfillJob.cdxLineToRow }
.debug
val existingKeys : TypedPipe[String] = hbaseSource
.read
.fromBytesWritable( new Fields("key") )
.toTypedPipe[String]('key)
//.debug
// filters out all the lines that have an existing SHA1 key in HBase
// the groupBy statements are to select key values to join on
val newRows : TypedPipe[(String, String, String, String)] = existingKeys
.groupBy( identity )
.rightJoin(cdxRows.groupBy(_._1))
.toTypedPipe
.collect { case (_, (None, row)) => row }
.debug
// convert to tuple form and write out into HBase
newRows
.toPipe('key, 'c, 'cdx, 'mime)
.toBytesWritable( new Fields("key", "c", "cdx", "mime") )
.write(hbaseSink)
}
object CdxBackfillJob {
def getHBaseSource(hbase_table: String, zookeeper_hosts: String) : HBaseSource = {
HBaseBuilder.build(
hbase_table,
zookeeper_hosts,
List("file:size"), // not actually needed
SourceMode.SCAN_ALL)
}
def getHBaseSink(hbase_table: String, zookeeper_hosts: String) : HBaseSource = {
HBaseBuilder.buildSink(
hbase_table,
zookeeper_hosts,
List("f:c", "file:cdx", "file:mime"),
SinkMode.UPDATE)
}
def normalizeMime(raw: String) : String = {
val NORMAL_MIME = List("application/pdf",
"application/postscript",
"text/html",
"text/xml")
val lower = raw.toLowerCase()
NORMAL_MIME.foreach(norm =>
if (lower.startsWith(norm)) {
return norm
}
)
// Common special cases
if (lower.startsWith("application/xml")) {
return "text/xml"
}
if (lower.startsWith("application/x-pdf")) {
return "application/pdf"
}
lower
}
def isCdxLine(line: String) : Boolean = {
// malformated or non-CDX11 lines
!(line.startsWith("#") || line.startsWith(" ") || line.startsWith("filedesc") ||
line.split(" ").size != 11)
}
def keepCdx(line: CdxLine) : Boolean = {
if (List(line.surt, line.datetime, line.url, line.mime, line.c_size, line.offset, line.warc).contains("-")) {
println("DASHLINE")
return false
}
// TODO: sha1.isalnum()
if (line.http_status != "200" || line.sha1.size != 32) {
return false
}
if (List(line.c_size, line.offset, line.datetime).map(s => Try(s.toLong).toOption).contains(None)) {
return false
}
return true
}
// Returns (key, f:c, file:cdx, file:mime), all as strings, which is close to
// how they will be inserted into HBase
def cdxLineToRow(line: CdxLine) : (String, String, String, String) = {
val key = "sha1:" + line.sha1
val warcFile = line.warc.split('/')(1)
// Read CDX-style datetime and conver to ISO 8601 with second resolution
val dtFormat = new java.text.SimpleDateFormat("yyyyMMddHHmmss")
val isoFormat = new java.text.SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss'Z'")
// TODO: timezones? UTC to UTC, so I don't think so.
val dtIso = isoFormat.format(dtFormat.parse(line.datetime))
// This is the "f:c" field. 'i' intentionally not set
// python: f:c = dict(u=url, d=dt_iso, f=warc_file, o=int(offset), c=1)
// python: warc_file = warc.split('/')[-1]
// python: dt_iso = datetime.strptime(dt, "%Y%m%d%H%M%S").isoformat()
val heritrixInfo = JSONObject(Map(
"u" -> line.url,
"d" -> dtIso,
"f" -> warcFile,
"o" -> line.offset.toInt,
"c" -> line.c_size.toInt
))
// python: dict(surt=surt, dt=dt, url=url, c_size=int(c_size),
// offset=int(offset), warc=warc)
val fileCdx = JSONObject(Map(
"surt" -> line.surt,
"dt" -> line.datetime,
"url" -> line.url,
"c_size" -> line.c_size.toInt,
"offset" -> line.offset.toInt,
"warc" -> line.warc
))
(key, heritrixInfo.toString(), fileCdx.toString(), normalizeMime(line.mime))
}
def lineToCdxLine(line: String) : CdxLine = {
val raw = line.split("\\s+")
// surt, datetime, url, mime, http_status, sha1, SKIP, SKIP, c_size, offset, warc
CdxLine(raw(0), raw(1), raw(2), raw(3), raw(4), raw(5), raw(8), raw(9), raw(10))
}
}
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